Method and apparatus to enable channel compression in advanced wireless communication systems

ABSTRACT

A method of a user equipment (UE) for a channel state information (CSI) feedback in a wireless communication system. The method comprises receiving, from a base station (BS), CSI feedback configuration information for the CSI feedback including a spatial channel information (SCI) indicator for each subband (SB), wherein the SCI indicator indicates a SCI associated with the downlink (DL) channel matrix; determining a CSI matrix HK,N comprising a dimension K×N based on the CSI feedback configuration information, where K indicates a number of SBs and N indicates a number of components of the SCI; identifying, based on the CSI matrix HK,N, the SCI indicator that indicates a first set of d basis vectors comprising a dimension K×1, a second set of d basis vectors comprising a dimension N×1, and a set of d coefficients, and transmitting, to the BS, the CSI feedback including the identified SCI indicator indicating the first set of d basis vectors, the second set of d basis vectors, and a set of d coefficients over an uplink channel.

CROSS-REFERENCE TO RELATED APPLICATIONS AND CLAIM OF PRIORITY

The present application is a continuation of U.S. patent applicationSer. No. 15/698,560, filed Sep. 7, 2017, which claims priority to U.S.Provisional Patent Application No. 62/394,320, filed on Sep. 14, 2016,the disclosures of which are incorporated herein by reference in theirentirety.

TECHNICAL FIELD

The present application relates generally to CSI acquisition at an eNBin advanced communication systems. More specifically, this disclosurerelates to explicit CSI acquisition to represent the channel in wirelesscommunication systems.

BACKGROUND

5th generation (5G) mobile communications, initial commercialization ofwhich is expected around 2020, is recently gathering increased momentumwith all the worldwide technical activities on the various candidatetechnologies from industry and academia. The candidate enablers for the5G mobile communications include massive antenna technologies, fromlegacy cellular frequency bands up to high frequencies, to providebeamforming gain and support increased capacity, new waveform (e.g., anew radio access technology (RAT)) to flexibly accommodate variousservices/applications with different requirements, new multiple accessschemes to support massive connections, and so on. The InternationalTelecommunication Union (ITU) has categorized the usage scenarios forinternational mobile telecommunications (IMT) for 2020 and beyond into 3main groups such as enhanced mobile broadband, massive machine typecommunications (MTC), and ultra-reliable and low latency communications.In addition, the ITC has specified target requirements such as peak datarates of 20 gigabit per second (Gb/s), user experienced data rates of100 megabit per second (Mb/s), a spectrum efficiency improvement of 3×,support for up to 500 kilometer per hour (km/h) mobility, 1 millisecond(ms) latency, a connection density of 106 devices/km2, a network energyefficiency improvement of 100× and an area traffic capacity of 10Mb/s/m2. While all the requirements need not be met simultaneously, thedesign of 5G networks may provide flexibility to support variousapplications meeting part of the above requirements on a use case basis.

SUMMARY

The present disclosure relates to a pre-5th-Generation (5G) or 5Gcommunication system to be provided for supporting higher data ratesbeyond 4th-Generation (4G) communication system such as long termevolution (LTE). Embodiments of the present disclosure provide multipleservices in advanced communication systems.

In one embodiment, a user equipment (UE) for a channel state information(CSI) feedback in a wireless communication system is provided. The UEcomprises a transceiver configure to receive, from a base station (BS),a CSI feedback configuration information for the CSI feedback includinga spatial channel information (SCI) indicator for each subband (SB),wherein the SCI indicator indicates a SCI associated with the downlink(DL) channel matrix. The UE further comprises at least one processorconfigured to determine a CSI matrix H_(K,N) comprising a dimension K×Nbased on the CSI feedback configuration information, where K indicates anumber of SBs and N indicates a number of components of the SCI;identify, based on the CSI matrix H_(K,N), the SCI indicator thatindicates a first set of d basis vectors comprising a dimension K×1, asecond set of d basis vectors comprising a dimension N×1, and a set of dcoefficients. The UE further comprises the transceiver configured totransmit, to the BS, the CSI feedback including the identified SCIindicator indicating the first set of d basis vectors, the second set ofd basis vectors, and a set of d coefficients over an uplink channel.

In another embodiment, a base station (BS) for a channel stateinformation (CSI) feedback in a wireless communication system isprovided. The BS comprises a transceiver configured to: transmit, to auser equipment (UE), a CSI feedback configuration information for theCSI feedback including a spatial channel information indicator (SCI) foreach subband (SB), wherein the SCI indicator indicates a SCI associatedwith the downlink (DL) channel matrix; and receive, from the UE, the CSIfeedback including the identified SCI indicator indicating the first setof d basis vectors, the second set of d basis vectors, and a set of dcoefficients over an uplink channel, wherein a CSI matrix H_(K,N)comprises a dimension K×N based on the CSI feedback configurationinformation, where K indicates a number of SBs and N indicates a numberof components of the SCI indicator, and wherein, based on the CSI matrixH_(K,N), the SCI indicator that indicates a first set of d basis vectorscomprising a dimension K×1, a second set of d basis vectors comprising adimension N×1, and a set of d coefficients.

In yet another embodiment, a method of a user equipment (UE) for achannel state information (CSI) feedback in a wireless communicationsystem is provided. The method comprises receiving, from a base station(BS), a CSI feedback configuration information for the CSI feedbackincluding a spatial channel information (SCI) indicator for each subband(SB), wherein the SCI indicator indicates a SCI associated with thedownlink (DL) channel matrix; determining a CSI matrix H_(K,N)comprising a dimension K×N based on the CSI feedback configurationinformation, where K indicates a number of SBs and N indicates a numberof components of the SCI; identifying, based on the CSI matrix H_(K,N),the SCI indicator that indicates a first set of d basis vectorscomprising a dimension K×1, a second set of d basis vectors comprising adimension N×1, and a set of d coefficients; and transmitting, to the BS,the CSI feedback including the identified SCI indicator indicating thefirst set of d basis vectors, the second set of d basis vectors, and aset of d coefficients over an uplink channel.

Other technical features may be readily apparent to one skilled in theart from the following figures, descriptions, and claims.

Before undertaking the DETAILED DESCRIPTION below, it may beadvantageous to set forth definitions of certain words and phrases usedthroughout this patent document. The term “couple” and its derivativesrefer to any direct or indirect communication between two or moreelements, whether or not those elements are in physical contact with oneanother. The terms “transmit,” “receive,” and “communicate,” as well asderivatives thereof, encompass both direct and indirect communication.The terms “include” and “comprise,” as well as derivatives thereof, meaninclusion without limitation. The term “or” is inclusive, meaningand/or. The phrase “associated with,” as well as derivatives thereof,means to include, be included within, interconnect with, contain, becontained within, connect to or with, couple to or with, be communicablewith, cooperate with, interleave, juxtapose, be proximate to, be boundto or with, have, have a property of, have a relationship to or with, orthe like. The term “controller” means any device, system or part thereofthat controls at least one operation. Such a controller may beimplemented in hardware or a combination of hardware and software and/orfirmware. The functionality associated with any particular controllermay be centralized or distributed, whether locally or remotely. Thephrase “at least one of,” when used with a list of items, means thatdifferent combinations of one or more of the listed items may be used,and only one item in the list may be needed. For example, “at least oneof: A, B, and C” includes any of the following combinations: A, B, C, Aand B, A and C, B and C, and A and B and C.

Moreover, various functions described below can be implemented orsupported by one or more computer programs, each of which is formed fromcomputer readable program code and embodied in a computer readablemedium. The terms “application” and “program” refer to one or morecomputer programs, software components, sets of instructions,procedures, functions, objects, classes, instances, related data, or aportion thereof adapted for implementation in a suitable computerreadable program code. The phrase “computer readable program code”includes any type of computer code, including source code, object code,and executable code. The phrase “computer readable medium” includes anytype of medium capable of being accessed by a computer, such as readonly memory (ROM), random access memory (RAM), a hard disk drive, acompact disc (CD), a digital video disc (DVD), or any other type ofmemory. A “non-transitory” computer readable medium excludes wired,wireless, optical, or other communication links that transporttransitory electrical or other signals. A non-transitory computerreadable medium includes media where data can be permanently stored andmedia where data can be stored and later overwritten, such as arewritable optical disc or an erasable memory device.

Definitions for other certain words and phrases are provided throughoutthis patent document. Those of ordinary skill in the art shouldunderstand that in many if not most instances, such definitions apply toprior as well as future uses of such defined words and phrases.

BRIEF DESCRIPTION OF THE DRAWINGS

For a more complete understanding of the present disclosure and itsadvantages, reference is now made to the following description taken inconjunction with the accompanying drawings, in which like referencenumerals represent like parts:

FIG. 1 illustrates an example wireless network according to embodimentsof the present disclosure;

FIG. 2 illustrates an example eNB according to embodiments of thepresent disclosure;

FIG. 3 illustrates an example UE according to embodiments of the presentdisclosure;

FIG. 4A illustrates an example high-level diagram of an orthogonalfrequency division multiple access transmit path according toembodiments of the present disclosure;

FIG. 4B illustrates an example high-level diagram of an orthogonalfrequency division multiple access receive path according to embodimentsof the present disclosure;

FIG. 5 illustrates an example network slicing according to embodimentsof the present disclosure;

FIG. 6 illustrates an example number of digital chains according toembodiments of the present disclosure;

FIG. 7 illustrates an example multiplexing two slices according toembodiments of the present disclosure;

FIG. 8 illustrates an example explicit CSI matrix and PCA basedcompression according to embodiments of the present disclosure;

FIG. 9 illustrates an example PCA based explicit CSI feedback reportingaccording to embodiments of the present disclosure;

FIG. 10 illustrates an example differential PCA in a time domainaccording to embodiments of the present disclosure;

FIG. 11 illustrates an example differential PCA based explicit CSIfeedback reporting according to embodiments of the present disclosure;

FIG. 12 illustrates an example differential PCA across SBs according toembodiments of the present disclosure;

FIG. 13 illustrates example differential PCA based on WB explicit CSIaccording to embodiments of the present disclosure;

FIG. 14 illustrates an example multi-panel antenna model according toembodiments of the present disclosure; and

FIG. 15 illustrates an example flow chart of a method for enablingchannel compression according to embodiments of the present disclosure.

DETAILED DESCRIPTION

FIG. 1 through FIG. 15, discussed below, and the various embodimentsused to describe the principles of the present disclosure in this patentdocument are by way of illustration only and should not be construed inany way to limit the scope of the disclosure. Those skilled in the artwill understand that the principles of the present disclosure may beimplemented in any suitably arranged system or device.

The following documents are hereby incorporated by reference into thepresent disclosure as if fully set forth herein: 3GPP TS 36.211 v13.0.0,“E-UTRA, Physical channels and modulation (REF 1);” 3GPP TS 36.212v13.0.0, “E-UTRA, Multiplexing and Channel coding; (REF 2);” 3GPP TS36.213 v13.0.0, “E-UTRA, Physical Layer Procedures (REF 3);” 3GPP TS36.321 v13.0.0, “E-UTRA, Medium Access Control (MAC) protocolspecification (REF 4);” 3GPP TS 36.331 v13.0.0, “Radio Resource Control(RRC) Protocol Specification (REF 5);” and 3GPP TR 22.891 v1.2.0,“Technical Specification Group Services and System Aspects; FeasibilityStudy on New Services and Markets Technology; Enablers; Stage 1;(Release 14).”

To meet the demand for wireless data traffic having increased sincedeployment of 4G communication systems, efforts have been made todevelop an improved 5G or pre-5G communication system. Therefore, the 5Gor pre-5G communication system is also called a “beyond 4G network” or a“post LTE system.”

The 5G communication system is considered to be implemented in higherfrequency (mmWave) bands, e.g., 60 GHz bands, so as to accomplish higherdata rates. To decrease propagation loss of the radio waves and increasethe transmission coverage, the beamforming, massive multiple-inputmultiple-output (MIMO), full dimensional MIMO (FD-MIMO), array antenna,an analog beam forming, large scale antenna techniques and the like arediscussed in 5G communication systems.

In addition, in 5G communication systems, development for system networkimprovement is under way based on advanced small cells, cloud radioaccess networks (RANs), ultra-dense networks, device-to-device (D2D)communication, wireless backhaul communication, moving network,cooperative communication, coordinated multi-points (CoMP) transmissionand reception, interference mitigation and cancellation and the like.

In the 5G system, hybrid frequency shift keying and quadrature amplitudemodulation (FQAM) and sliding window superposition coding (SWSC) as anadaptive modulation and coding (AMC) technique, and filter bank multicarrier (FBMC), non-orthogonal multiple access (NOMA), and sparse codemultiple access (SCMA) as an advanced access technology have beendeveloped.

FIGS. 1-4B below describe various embodiments implemented in wirelesscommunications systems and with the use of orthogonal frequency divisionmultiplexing (OFDM) or orthogonal frequency division multiple access(OFDMA) communication techniques. The descriptions of FIGS. 1-3 are notmeant to imply physical or architectural limitations to the manner inwhich different embodiments may be implemented. Different embodiments ofthe present disclosure may be implemented in any suitably-arrangedcommunications system.

FIG. 1 illustrates an example wireless network according to embodimentsof the present disclosure. The embodiment of the wireless network shownin FIG. 1 is for illustration only. Other embodiments of the wirelessnetwork 100 could be used without departing from the scope of thisdisclosure.

As shown in FIG. 1, the wireless network includes an eNB 101, an eNB102, and an eNB 103. The eNB 101 communicates with the eNB 102 and theeNB 103. The eNB 101 also communicates with at least one network 130,such as the Internet, a proprietary Internet Protocol (IP) network, orother data network.

The eNB 102 provides wireless broadband access to the network 130 for afirst plurality of user equipments (UEs) within a coverage area 120 ofthe eNB 102. The first plurality of UEs includes a UE 111, which may belocated in a small business (SB); a UE 112, which may be located in anenterprise (E); a UE 113, which may be located in a WiFi hotspot (HS); aUE 114, which may be located in a first residence (R); a UE 115, whichmay be located in a second residence (R); and a UE 116, which may be amobile device (M), such as a cell phone, a wireless laptop, a wirelessPDA, or the like. The eNB 103 provides wireless broadband access to thenetwork 130 for a second plurality of UEs within a coverage area 125 ofthe eNB 103. The second plurality of UEs includes the UE 115 and the UE116. In some embodiments, one or more of the eNBs 101-103 maycommunicate with each other and with the UEs 111-116 using 5G, LTE,LTE-A, WiMAX, WiFi, or other wireless communication techniques.

Depending on the network type, the term “base station” or “BS” can referto any component (or collection of components) configured to providewireless access to a network, such as transmit point (TP),transmit-receive point (TRP), an enhanced base station (eNodeB or eNB),a 5G base station (gNB), a macrocell, a femtocell, a WiFi access point(AP), or other wirelessly enabled devices. Base stations may providewireless access in accordance with one or more wireless communicationprotocols, e.g., 5G 3GPP new radio interface/access (NR), long termevolution (LTE), LTE advanced (LTE-A), high speed packet access (HSPA),Wi-Fi 802.11a/b/g/n/ac, etc. For the sake of convenience, the terms “BS”and “TRP” are used interchangeably in this patent document to refer tonetwork infrastructure components that provide wireless access to remoteterminals. Also, depending on the network type, the term “userequipment” or “UE” can refer to any component such as “mobile station,”“subscriber station,” “remote terminal,” “wireless terminal,” “receivepoint,” or “user device.” For the sake of convenience, the terms “userequipment” and “UE” are used in this patent document to refer to remotewireless equipment that wirelessly accesses a BS, whether the UE is amobile device (such as a mobile telephone or smartphone) or is normallyconsidered a stationary device (such as a desktop computer or vendingmachine).

Dotted lines show the approximate extents of the coverage areas 120 and125, which are shown as approximately circular for the purposes ofillustration and explanation only. It should be clearly understood thatthe coverage areas associated with eNBs, such as the coverage areas 120and 125, may have other shapes, including irregular shapes, dependingupon the configuration of the eNBs and variations in the radioenvironment associated with natural and man-made obstructions.

As described in more detail below, one or more of the UEs 111-116include circuitry, programming, or a combination thereof, for efficientCSI reporting on PUCCH in an advanced wireless communication system. Incertain embodiments, and one or more of the eNBs 101-103 includescircuitry, programming, or a combination thereof, for receivingefficient CSI reporting on PUCCH in an advanced wireless communicationsystem.

Although FIG. 1 illustrates one example of a wireless network, variouschanges may be made to FIG. 1. For example, the wireless network couldinclude any number of eNBs and any number of UEs in any suitablearrangement. Also, the eNB 101 could communicate directly with anynumber of UEs and provide those UEs with wireless broadband access tothe network 130. Similarly, each eNB 102-103 could communicate directlywith the network 130 and provide UEs with direct wireless broadbandaccess to the network 130. Further, the eNBs 101, 102, and/or 103 couldprovide access to other or additional external networks, such asexternal telephone networks or other types of data networks.

FIG. 2 illustrates an example eNB 102 according to embodiments of thepresent disclosure. The embodiment of the eNB 102 illustrated in FIG. 2is for illustration only, and the eNBs 101 and 103 of FIG. 1 could havethe same or similar configuration. However, eNBs come in a wide varietyof configurations, and FIG. 2 does not limit the scope of thisdisclosure to any particular implementation of an eNB.

As shown in FIG. 2, the eNB 102 includes multiple antennas 205 a-205 n,multiple RF transceivers 210 a-210 n, transmit (TX) processing circuitry215, and receive (RX) processing circuitry 220. The eNB 102 alsoincludes a controller/processor 225, a memory 230, and a backhaul ornetwork interface 235.

The RF transceivers 210 a-210 n receive, from the antennas 205 a-205 n,incoming RF signals, such as signals transmitted by UEs in the network100. The RF transceivers 210 a-210 n down-convert the incoming RFsignals to generate IF or baseband signals. The IF or baseband signalsare sent to the RX processing circuitry 220, which generates processedbaseband signals by filtering, decoding, and/or digitizing the basebandor IF signals. The RX processing circuitry 220 transmits the processedbaseband signals to the controller/processor 225 for further processing.

In some embodiments, the RF transceiver 210 a-201 n is capable oftransmitting CSI feedback configuration information for the CSI feedbackincluding a spatial channel information indicator for each subband (SB).In such embodiment, the spatial channel information indicator comprisesat least one of a downlink channel matrix, a covariance matrix of thedownlink channel matrix, or an eigenvector of the covariance matrix ofthe downlink channel matrix.

In some embodiments, the RF transceiver 210 a-201 n is capable ofreceiving the CSI feedback including the spatial channel informationindicator indicating U_(d), V_(d), and Σ_(d) over an uplink channel anda first CSI feedback including the first spatial channel informationindicator indicating U_(d) ₁ , V_(d) ₁ , and Σ_(d) ₁ and, over eitherthe first uplink channel or a second uplink channel, a second CSIfeedback including the second spatial channel information indicatorindicating U_(d) ₂ , V_(d) ₂ , and Σ_(d) ₂ .

The TX processing circuitry 215 receives analog or digital data (such asvoice data, web data, e-mail, or interactive video game data) from thecontroller/processor 225. The TX processing circuitry 215 encodes,multiplexes, and/or digitizes the outgoing baseband data to generateprocessed baseband or IF signals. The RF transceivers 210 a-210 nreceive the outgoing processed baseband or IF signals from the TXprocessing circuitry 215 and up-converts the baseband or IF signals toRF signals that are transmitted via the antennas 205 a-205 n.

The controller/processor 225 can include one or more processors or otherprocessing devices that control the overall operation of the eNB 102.For example, the controller/processor 225 could control the reception offorward channel signals and the transmission of reverse channel signalsby the RF transceivers 210 a-210 n, the RX processing circuitry 220, andthe TX processing circuitry 215 in accordance with well-knownprinciples. The controller/processor 225 could support additionalfunctions as well, such as more advanced wireless communicationfunctions. For instance, the controller/processor 225 could support beamforming or directional routing operations in which outgoing signals frommultiple antennas 205 a-205 n are weighted differently to effectivelysteer the outgoing signals in a desired direction. Any of a wide varietyof other functions could be supported in the eNB 102 by thecontroller/processor 225.

The controller/processor 225 is also capable of executing programs andother processes resident in the memory 230, such as an OS. Thecontroller/processor 225 can move data into or out of the memory 230 asrequired by an executing process.

The controller/processor 225 is also coupled to the backhaul or networkinterface 235. The backhaul or network interface 235 allows the eNB 102to communicate with other devices or systems over a backhaul connectionor over a network. The interface 235 could support communications overany suitable wired or wireless connection(s). For example, when the eNB102 is implemented as part of a cellular communication system (such asone supporting 5G, LTE, or LTE-A), the interface 235 could allow the eNB102 to communicate with other eNBs over a wired or wireless backhaulconnection. When the eNB 102 is implemented as an access point, theinterface 235 could allow the eNB 102 to communicate over a wired orwireless local area network or over a wired or wireless connection to alarger network (such as the Internet). The interface 235 includes anysuitable structure supporting communications over a wired or wirelessconnection, such as an Ethernet or RF transceiver.

The memory 230 is coupled to the controller/processor 225. Part of thememory 230 could include a RAM, and another part of the memory 230 couldinclude a Flash memory or other ROM.

Although FIG. 2 illustrates one example of eNB 102, various changes maybe made to FIG. 2. For example, the eNB 102 could include any number ofeach component shown in FIG. 2. As a particular example, an access pointcould include a number of interfaces 235, and the controller/processor225 could support routing functions to route data between differentnetwork addresses. As another particular example, while shown asincluding a single instance of TX processing circuitry 215 and a singleinstance of RX processing circuitry 220, the eNB 102 could includemultiple instances of each (such as one per RF transceiver). Also,various components in FIG. 2 could be combined, further subdivided, oromitted and additional components could be added according to particularneeds.

FIG. 3 illustrates an example UE 116 according to embodiments of thepresent disclosure. The embodiment of the UE 116 illustrated in FIG. 3is for illustration only, and the UEs 111-115 of FIG. 1 could have thesame or similar configuration. However, UEs come in a wide variety ofconfigurations, and FIG. 3 does not limit the scope of this disclosureto any particular implementation of a UE.

As shown in FIG. 3, the UE 116 includes an antenna 305, a radiofrequency (RF) transceiver 310, TX processing circuitry 315, amicrophone 320, and receive (RX) processing circuitry 325. The UE 116also includes a speaker 330, a processor 340, an input/output (I/O)interface (IF) 345, a touchscreen 350, a display 355, and a memory 360.The memory 360 includes an operating system (OS) 361 and one or moreapplications 362.

The RF transceiver 310 receives, from the antenna 305, an incoming RFsignal transmitted by an eNB of the network 100. The RF transceiver 310down-converts the incoming RF signal to generate an intermediatefrequency (IF) or baseband signal. The IF or baseband signal is sent tothe RX processing circuitry 325, which generates a processed basebandsignal by filtering, decoding, and/or digitizing the baseband or IFsignal. The RX processing circuitry 325 transmits the processed basebandsignal to the speaker 330 (such as for voice data) or to the processor340 for further processing (such as for web browsing data).

In some embodiments, the RF transceiver 310 is capable of receiving CSIfeedback configuration information for the CSI feedback including aspatial channel information indicator for each subband (SB). In suchembodiments, the spatial channel information indicator comprises atleast one of a downlink channel matrix, a covariance matrix of thedownlink channel matrix, or an eigenvector of the covariance matrix ofthe downlink channel matrix.

In some embodiments, the RF transceiver 310 is capable of transmittingthe CSI feedback including the spatial channel information indicatorindicating U_(d), V_(d), and Σ_(d) over an uplink channel and, over afirst uplink channel, a first CSI feedback including the first spatialchannel information indicator indicating U_(d) ₁ , V_(d) ₁ , and Σ_(d) ₁and, over either the first uplink channel or a second uplink channel, asecond CSI feedback including the second spatial channel informationindicator indicating U_(d) ₂ , V_(d) ₂ , and Σ_(d) ₂ .

The TX processing circuitry 315 receives analog or digital voice datafrom the microphone 320 or other outgoing baseband data (such as webdata, e-mail, or interactive video game data) from the processor 340.The TX processing circuitry 315 encodes, multiplexes, and/or digitizesthe outgoing baseband data to generate a processed baseband or IFsignal. The RF transceiver 310 receives the outgoing processed basebandor IF signal from the TX processing circuitry 315 and up-converts thebaseband or IF signal to an RF signal that is transmitted via theantenna 305.

The processor 340 can include one or more processors or other processingdevices and execute the OS 361 stored in the memory 360 in order tocontrol the overall operation of the UE 116. For example, the processor340 could control the reception of forward channel signals and thetransmission of reverse channel signals by the RF transceiver 310, theRX processing circuitry 325, and the TX processing circuitry 315 inaccordance with well-known principles. In some embodiments, theprocessor 340 includes at least one microprocessor or microcontroller.

The processor 340 is also capable of executing other processes andprograms resident in the memory 360, such as processes for CSI reportingon PUCCH. The processor 340 can move data into or out of the memory 360as required by an executing process. In some embodiments, the processor340 is configured to execute the applications 362 based on the OS 361 orin response to signals received from eNBs or an operator. The processor340 is also coupled to the I/O interface 345, which provides the UE 116with the ability to connect to other devices, such as laptop computersand handheld computers. The I/O interface 345 is the communication pathbetween these accessories and the processor 340.

In some embodiments, the processor 340 is also capable of determining aCSI matrix H_(K,N) comprising a dimension K×N based on the CSI feedbackconfiguration information, identifying, based on the CSI matrix H_(K,N),the spatial channel information indicator.

In some embodiments, the processor 340 is also capable of identifyingthe spatial channel information indicator based on a set of d triples{(u_(i), v_(i), σ_(i)): 0≤i≤d−1}, the spatial channel informationindicator based on a set of d pairs {(w_(i), σ_(i)): 0≤i≤d−1}, thespatial channel information indicator based on a triple of matrices(U_(d), V_(d), Σ_(d)), and identifying the spatial channel informationindicator based on a codebook for at least one of U_(d), V_(d), orΣ_(d).

In some embodiments, the processor 340 is also capable of identifying afirst spatial channel information indicator indicating U_(d) ₁ , V_(d) ₁, and Σ_(d) ₁ based on a first CSI matrix H_(K,N) ⁽¹⁾ and a secondspatial channel information indicator indicating U_(d) ₂ , V_(d) ₂ , andΣ_(d) ₂ based on a difference H_(K,N) ⁽²⁾−{tilde over (H)}_(K,N) ⁽¹⁾between a second CSI matrix H_(K,N) ⁽²⁾ and a representation {tilde over(H)}_(K,N) ⁽¹⁾ of the first CSI matrix H_(K,N) ⁽¹⁾ according to thefirst spatial channel information indicator.

The processor 340 is also coupled to the touchscreen 350 and the display355. The operator of the UE 116 can use the touchscreen 350 to enterdata into the UE 116. The display 355 may be a liquid crystal display,light emitting diode display, or other display capable of rendering textand/or at least limited graphics, such as from web sites.

The memory 360 is coupled to the processor 340. Part of the memory 360could include a random access memory (RAM), and another part of thememory 360 could include a Flash memory or other read-only memory (ROM).

Although FIG. 3 illustrates one example of UE 116, various changes maybe made to FIG. 3. For example, various components in FIG. 3 could becombined, further subdivided, or omitted and additional components couldbe added according to particular needs. As a particular example, theprocessor 340 could be divided into multiple processors, such as one ormore central processing units (CPUs) and one or more graphics processingunits (GPUs). Also, while FIG. 3 illustrates the UE 116 configured as amobile telephone or smartphone, UEs could be configured to operate asother types of mobile or stationary devices.

FIG. 4A is a high-level diagram of transmit path circuitry. For example,the transmit path circuitry may be used for an orthogonal frequencydivision multiple access (OFDMA) communication. FIG. 4B is a high-leveldiagram of receive path circuitry. For example, the receive pathcircuitry may be used for an orthogonal frequency division multipleaccess (OFDMA) communication. In FIGS. 4A and 4B, for downlinkcommunication, the transmit path circuitry may be implemented in a basestation (eNB) 102 or a relay station, and the receive path circuitry maybe implemented in a user equipment (e.g. user equipment 116 of FIG. 1).In other examples, for uplink communication, the receive path circuitry450 may be implemented in a base station (e.g. eNB 102 of FIG. 1) or arelay station, and the transmit path circuitry may be implemented in auser equipment (e.g. user equipment 116 of FIG. 1).

Transmit path circuitry comprises channel coding and modulation block405, serial-to-parallel (S-to-P) block 410, Size N Inverse Fast FourierTransform (IFFT) block 415, parallel-to-serial (P-to-S) block 420, addcyclic prefix block 425, and up-converter (UC) 430. Receive pathcircuitry 450 comprises down-converter (DC) 455, remove cyclic prefixblock 460, serial-to-parallel (S-to-P) block 465, Size N Fast FourierTransform (FFT) block 470, parallel-to-serial (P-to-S) block 475, andchannel decoding and demodulation block 480.

At least some of the components in FIGS. 4A 400 and 4B 450 may beimplemented in software, while other components may be implemented byconfigurable hardware or a mixture of software and configurablehardware. In particular, it is noted that the FFT blocks and the IFFTblocks described in this disclosure document may be implemented asconfigurable software algorithms, where the value of Size N may bemodified according to the implementation.

Furthermore, although this disclosure is directed to an embodiment thatimplements the Fast Fourier Transform and the Inverse Fast FourierTransform, this is by way of illustration only and may not be construedto limit the scope of the disclosure. It will be appreciated that in analternate embodiment of the disclosure, the Fast Fourier Transformfunctions and the Inverse Fast Fourier Transform functions may easily bereplaced by discrete Fourier transform (DFT) functions and inversediscrete Fourier transform (IDFT) functions, respectively. It will beappreciated that for DFT and IDFT functions, the value of the N variablemay be any integer number (i.e., 1, 4, 3, 4, etc.), while for FFT andIFFT functions, the value of the N variable may be any integer numberthat is a power of two (i.e., 1, 2, 4, 8, 16, etc.).

In transmit path circuitry 400, channel coding and modulation block 405receives a set of information bits, applies coding (e.g., LDPC coding)and modulates (e.g., quadrature phase shift keying (QPSK) or quadratureamplitude modulation (QAM)) the input bits to produce a sequence offrequency-domain modulation symbols. Serial-to-parallel block 410converts (i.e., de-multiplexes) the serial modulated symbols to paralleldata to produce N parallel symbol streams where N is the IFFT/FFT sizeused in BS 102 and UE 116. Size N IFFT block 415 then performs an IFFToperation on the N parallel symbol streams to produce time-domain outputsignals. Parallel-to-serial block 420 converts (i.e., multiplexes) theparallel time-domain output symbols from Size N IFFT block 415 toproduce a serial time-domain signal. Add cyclic prefix block 425 theninserts a cyclic prefix to the time-domain signal. Finally, up-converter430 modulates (i.e., up-converts) the output of add cyclic prefix block425 to RF frequency for transmission via a wireless channel. The signalmay also be filtered at baseband before conversion to RF frequency.

The transmitted RF signal arrives at UE 116 after passing through thewireless channel, and reverse operations to those at eNB 102 areperformed. Down-converter 455 down-converts the received signal tobaseband frequency, and remove cyclic prefix block 460 removes thecyclic prefix to produce the serial time-domain baseband signal.Serial-to-parallel block 465 converts the time-domain baseband signal toparallel time-domain signals. Size N FFT block 470 then performs an FFTalgorithm to produce N parallel frequency-domain signals.Parallel-to-serial block 475 converts the parallel frequency-domainsignals to a sequence of modulated data symbols. Channel decoding anddemodulation block 480 demodulates and then decodes the modulatedsymbols to recover the original input data stream.

Each of eNBs 101-103 may implement a transmit path that is analogous totransmitting in the downlink to user equipment 111-116 and may implementa receive path that is analogous to receiving in the uplink from userequipment 111-116. Similarly, each one of user equipment 111-116 mayimplement a transmit path corresponding to the architecture fortransmitting in the uplink to eNBs 101-103 and may implement a receivepath corresponding to the architecture for receiving in the downlinkfrom eNBs 101-103.

Various embodiments of the present disclosure provides for ahigh-performance, scalability with respect to the number and geometry oftransmit antennas, and a flexible CSI feedback (e.g., reporting)framework and structure for LTE enhancements when FD-MIMO with largetwo-dimensional antenna arrays is supported. To achieve highperformance, more accurate CSI in terms MIMO channel is needed at theeNB especially for FDD scenarios. In this case, embodiments of thepresent disclosure recognize that the previous LTE specificationprecoding framework (PMI-based feedback) may need to be replaced. Inthis disclosure, properties of FD-MIMO are factored in for the presentdisclosure. For example, the use of closely spaced large 2D antennaarrays that is primarily geared toward high beamforming gain rather thanspatial multiplexing along with relatively small angular spread for eachUE. Therefore, compression or dimensionality reduction of the channelfeedback in accordance with a fixed set of basic functions and vectorsmay be achieved. In another example, updated channel feedback parameters(e.g., the channel angular spreads) may be obtained at low mobilityusing UE-specific higher-layer signaling. In addition, a CSI reporting(feedback) may also be performed cumulatively.

Another embodiment of the present disclosure incorporates a CSIreporting method and procedure with a reduced PMI feedback. This PMIreporting at a lower rate pertains to long-term DL channel statisticsand represents a choice of a group of precoding vectors recommended by aUE to an eNB. The present disclosure also includes a DL transmissionscheme wherein an eNB transmits data to a UE over a plurality ofbeamforming vectors while utilizing an open-loop diversity scheme.Accordingly, the use of long-term precoding ensures that open-looptransmit diversity is applied only across a limited number of ports(rather than all the ports available for FD-MIMO, e.g., 64). This avoidshaving to support excessively high dimension for open-loop transmitdiversity that reduces CSI feedback overhead and improves robustnesswhen CSI measurement quality is questionable.

5G communication system use cases have been identified and described.Those use cases can be roughly categorized into three different groups.In one example, enhanced mobile broadband (eMBB) is determined to dowith high bits/sec requirement, with less stringent latency andreliability requirements. In another example, ultra reliable and lowlatency (URLL) is determined with less stringent bits/sec requirement.In yet another example, massive machine type communication (mMTC) isdetermined that a number of devices can be as many as 100,000 to 1million per km2, but the reliability/throughput/latency requirementcould be less stringent. This scenario may also involve power efficiencyrequirement as well, in that the battery consumption should be minimizedas possible.

In LTE technologies, a time interval X which can contain one or more ofthe DL transmission part, guard, UL transmission part, and a combinationof thereof regardless of they are indicated dynamically and/orsemi-statically. Furthermore, in one example, the DL transmission partof time interval X contains downlink control information and/or downlinkdata transmissions and/or reference signals. In another example, the ULtransmission part of time interval X contains uplink control informationand/or uplink data transmissions and/or reference signals. In addition,the usage of DL and UL does not preclude other deployment scenariose.g., sidelink, backhaul, relay). In some embodiments of the currentdisclosure, “a subframe” is another name to refer to “a time intervalX,” or vice versa. In order for the 5G network to support these diverseservices are called network slicing.

In some embodiments, “a subframe” and “a time slot” can be usedinterchangeably. In some embodiments, “a subframe” refers to a transmittime interval (TTI), which may comprise an aggregation of “time slots”for UE”s data transmission/reception.

FIG. 5 illustrates a network slicing 500 according to embodiments of thepresent disclosure. An embodiment of the network slicing 500 shown inFIG. 5 is for illustration only. One or more of the componentsillustrated in FIG. 5 can be implemented in specialized circuitryconfigured to perform the noted functions or one or more of thecomponents can be implemented by one or more processors executinginstructions to perform the noted functions. Other embodiments are usedwithout departing from the scope of the present disclosure.

As shown in FIG. 5, the network slicing 500 comprises an operator'snetwork 510, a plurality of RANS 520, a plurality of eNBs 530 a, 530 b,a plurality of small cell base stations 535 a, 535 b, a URLL slice 540a, a smart watch 545 a, a car 545 b, a, truck 545 c, a smart glasses 545d, a power 555 a, a temperature 555 b, an mMTC slice 550 a, an eMBBslice 560 a, a smart phone (e.g., cell phones) 565 a, a laptop 565 b,and a tablet 565 c (e.g., tablet PCs).

The operator's network 510 includes a number of radio access network(s)520—RAN(s)—that are associated with network devices, e.g., eNBs 530 aand 530 b, small cell base stations (femto/pico eNBs or Wi-Fi accesspoints) 535 a and 535 b, etc. The operator's network 510 can supportvarious services relying on the slice concept. In one example, fourslices, 540 a, 550 a, 550 b and 560 a, are supported by the network. TheURLL slice 540 a to serve UEs requiring URLL services, e.g., cars 545 b,trucks 545 c, smart watches 545 a, smart glasses 545 d, etc. Two mMTCslices 550 a and 550 b serve UEs requiring mMTC services such as powermeters and temperature control (e.g., 555 b), and one eMBB slice 560 arequiring eMBB serves such as cells phones 565 a, laptops 565 b, tablets565 c.

In short, network slicing is a method to cope with various differentqualities of services (QoS) in the network level. For supporting thesevarious QoS efficiently, slice-specific PHY optimization may also benecessary. Devices 545 a/b/c/d, 555 a/b are 565 a/b/c examples of userequipment (UE) of different types. The different types of user equipment(UE) shown in FIG. 5 are not necessarily associated with particulartypes of slices. For example, the cell phone 565 a, the laptop 565 b andthe tablet 565 c are associated with the eMBB slice 560 a, but this isjust for illustration and these devices can be associated with any typesof slices.

In some embodiments, one device is configured with more than one slice.In one embodiment, the UE, (e.g., 565 a/b/c) is associated with twoslices, the URLL slice 540 a and the eMBB slice 560 a. This can beuseful for supporting online gaming application, in which graphicalinformation are transmitted through the eMBB slice 560 a, and userinteraction related information are exchanged through the URLL slice 540a.

In the current LTE standard, no slice-level PHY is available, and mostof the PHY functions are utilized slice-agnostic. A UE is typicallyconfigured with a single set of PHY parameters (including transmit timeinterval (TTI) length, OFDM symbol length, subcarrier spacing, etc.),which is likely to prevent the network from (1) fast adapting todynamically changing QoS; and (2) supporting various QoS simultaneously.

In some embodiments, corresponding PHY designs to cope with differentQoS with network slicing concept are disclosed. It is noted that “slice”is a terminology introduced just for convenience to refer to a logicalentity that is associated with common features, for example, numerology,an upper-layer (including medium access control/radio resource control(MAC/RRC)), and shared UL/DL time-frequency resources. Alternative namesfor “slice” include virtual cells, hyper cells, cells, etc.

FIG. 6 illustrates an example number of digital chains 600 according toembodiments of the present disclosure. An embodiment of the number ofdigital chains 600 shown in FIG. 6 is for illustration only. One or moreof the components illustrated in FIG. 6 can be implemented inspecialized circuitry configured to perform the noted functions or oneor more of the components can be implemented by one or more processorsexecuting instructions to perform the noted functions. Other embodimentsare used without departing from the scope of the present disclosure.

LTE specification supports up to 32 CSI-RS antenna ports which enable aneNB to be equipped with a large number of antenna elements (such as 64or 128). In this case, a plurality of antenna elements is mapped ontoone CSI-RS port. For next generation cellular systems such as 5G, themaximum number of CSI-RS ports can either remain the same or increase.

For mmWave bands, although the number of antenna elements can be largerfor a given form factor, the number of CSI-RS ports—which can correspondto the number of digitally precoded ports—tends to be limited due tohardware constraints (such as the feasibility to install a large numberof ADCs/DACs at mmWave frequencies) as illustrated in FIG. 6. In thiscase, one CSI-RS port is mapped onto a large number of antenna elementswhich can be controlled by a bank of analog phase shifters 601. OneCSI-RS port can then correspond to one sub-array which produces a narrowanalog beam through analog beamforming 605. This analog beam can beconfigured to sweep across a wider range of angles 620 by varying thephase shifter bank across symbols or subframes. The number of sub-arrays(equal to the number of RF chains) is the same as the number of CSI-RSports N_(CSI-PORT). A digital beamforming unit 610 performs a linearcombination across N_(CSI-PORT) analog beams to further increaseprecoding gain. While analog beams are wideband (hence notfrequency-selective), digital precoding can be varied across frequencysub-bands or resource blocks.

To enable digital precoding, an efficient design of CSI-RS is a crucialfactor. For this reason, three types of CSI reporting mechanismcorresponding to three types of CSI-RS measurement behavior aresupported in LTE specification) “CLASS A” CSI reporting whichcorresponds to non-precoded CSI-RS, 2) “CLASS B” reporting with K=1CSI-RS resource which corresponds to UE-specific beamformed CSI-RS, 3)“CLASS B” reporting with K>1 CSI-RS resources which corresponds tocell-specific beamformed CSI-RS.

For non-precoded (NP) CSI-RS, a cell-specific one-to-one mapping betweenCSI-RS port and TXRU is utilized. Here, different CSI-RS ports have thesame wide beam width and direction and hence generally cell widecoverage. For beamformed CSI-RS, beamforming operation, eithercell-specific or UE-specific, is applied on a non-zero-power (NZP)CSI-RS resource (consisting of multiple ports). Here, (at least at agiven time/frequency) CSI-RS ports have narrow beam widths and hence notcell wide coverage, and (at least from the eNB perspective) at leastsome CSI-RS port-resource combinations have different beam directions.

In scenarios where DL long-term channel statistics can be measuredthrough UL signals at a serving eNodeB, UE-specific BF CSI-RS can bereadily used. This is typically feasible when UL-DL duplex distance issufficiently small. When this condition does not hold, however, some UEfeedback is necessary for the eNodeB to obtain an estimate of DLlong-term channel statistics (or any of representation of theDL-long-term channel statistics). To facilitate such a procedure, afirst BF CSI-RS transmitted with periodicity T1 (ms) and a second NPCSI-RS transmitted with periodicity T2 (ms), where T1≤T2. This approachis termed hybrid CSI-RS. The implementation of hybrid CSI-RS is largelydependent on the definition of CSI process and NZP CSI-RS resource.

In LTE specification for eFD-MIMO, MIMO has been identified as anessential feature in order to achieve high system throughputrequirements and MIMO may continue to be the same in NR. One of the keycomponents of a MIMO transmission scheme is the accurate CSI acquisitionat the eNB (or TRP). For MU-MIMO, in particular, the availability ofaccurate CSI is necessary in order to guarantee high MU performance. ForTDD systems, the CSI can be acquired using the SRS transmission relyingon the channel reciprocity. For FDD systems, on the other hand, it canbe acquired using the CSI-RS transmission from eNB, and CSI acquisitionand feedback from UE. In legacy (up to LTE specification) FDD systems,the CSI feedback framework is “implicit” in the form of CQI/PMI/RI (andCRI in the LTE specification) derived from a codebook assuming SUtransmission from eNB. Because of the inherent SU assumption whilederiving CSI, this implicit CSI feedback is inadequate for MUtransmission.

Since future (e.g. NR) systems are likely to be more MU-centric, thisSU-MU CSI mismatch may be a bottleneck in achieving high MU performancegains. Another issue with implicit feedback is the scalability withlarger number of antenna ports at eNB. For large number of antennaports, the codebook design for implicit feedback is quite complicated(for example, in the LTE specification, the total number of Class Acodebooks=44), and the designed codebook is not guaranteed to bringjustifiable performance benefits in practical deployment scenarios (forexample, only a small percentage gain can be shown at the most).Realizing aforementioned issues, RAN1 has agreed to providespecification support to advanced CSI reporting in the LTE specificationof eFD-MIMO, which, at the very least, can serve as a good startingpoint to design advanced CSI scheme in NR MIMO.

FIG. 7 illustrates an example multiplexing two slices 700 according toembodiments of the present disclosure. An embodiment of the multiplexingtwo slices 700 shown in FIG. 7 is for illustration only. One or more ofthe components illustrated in FIG. 7 can be implemented in specializedcircuitry configured to perform the noted functions or one or more ofthe components can be implemented by one or more processors executinginstructions to perform the noted functions. Other embodiments are usedwithout departing from the scope of the present disclosure.

To utilize PHY resources efficiently and multiplex various slices (withdifferent resource allocation schemes, numerologies, and schedulingstrategies) in DL-SCH, a flexible and self-contained frame or subframedesign is utilized. Two exemplary instances of multiplexing two sliceswithin a common subframe or frame are depicted in FIG. 7. In FIG. 7, aslice can be composed of one or two transmission instances where onetransmission instance consists of a control (CTRL) component (720 a, 760a, 760 b, 720 b, and 760 c) and a data component (730 a, 770 a, 770 b,730 b, and 770 c). In FIG. 7, the two slides (e.g., 710) are multiplexedin frequency domain whereas slices are multiplexed in time domain (e.g.,750).

Compared to LTE specification, the CSI acquisition for NR MIMO mayconsider the following additional differentiating factors. In oneexample of increased number of antenna ports for NR MIMO, the number ofantenna elements at the eNB can be up to 256, which means that the totalnumber of antenna ports can be more than 32, which is the maximum numberof antenna ports supported in LTE specification. Although this can beaccommodated with partial-port CSI-RS mapping where each subset consistsof at most 32 ports, the total number of ports across time can beextended to a much larger number. As the number of ports increases,meaningful system gain can only be obtained in a MU-centric system.

In another example of increased throughput requirement, the systemthroughput requirements (e.g. for eMBB in NR) is several times more thanthat for LTE specification eFD-MIMO. Such high throughput requirementscan only met with a mechanism to provide very accurate CSI to the eNB.

In yet another example of beamforming, FD-MIMO and NR MIMO system may bebeam-formed either cell-specifically or UE-specifically, where the beamscan either be of analog (RF) or digital or hybrid type. For such abeam-formed system, a mechanism is needed to obtain accuratebeam-forming information at the eNB.

In yet another example of Unified design, since NR includes both aboveand below 6 GHz frequency bands, a unified MIMO framework working forboth frequency regimes may be preferable.

In view of the aforementioned embodiments with the implicit feedbackparadigm and the additional differentiating factors specific with NRMIMO, it may be observed that the implicit CSI feedback scheme alone isnot enough for NR MIMO, and hence advanced CSI is needed.

In some embodiment 0, a UE is configured to report “explicit CSI” suchas channel, dominant eigenvectors, and covariance matrix for eachsubband (SB) based on compression techniques such as principal componentanalysis (PCA) in order to exploit correlation in spatial (acrossantennas) and frequency (across SBs) domains jointly, where a SBcorresponds to multiple (p) consecutive PRBs and the number p depends onthe system bandwidth (BW), for example, p=6 for 20 MHz BW.

FIG. 8 illustrates an example explicit CSI matrix and PCA 800 basedcompression according to embodiments of the present disclosure. Anembodiment of the explicit CSI matrix and PCA 800 shown in FIG. 8 is forillustration only. One or more of the components illustrated in FIG. 8can be implemented in specialized circuitry configured to perform thenoted functions or one or more of the components can be implemented byone or more processors executing instructions to perform the notedfunctions. Other embodiments are used without departing from the scopeof the present disclosure.

An illustration of the proposed PCA based explicit CSI compression isshown in FIG. 8. Let N be the number of explicit CSI components thatneed to be reported in each SB. The number N depends on the explicit CSItype as follows: Channel: N=2N₁N₂×N_(r)×k, Eigenvectors: N=2N₁N₂×r, andCovariance matrix: N=2N₁N₂×2N₁N₂, where 2N₁N₂ is the number of antennaports at eNB (or gNB), N_(r) is the number of antennas at the UE, r isthe number of dominant eigenvectors, and k is the number of subcarriersin a SB for which the DL channel is explicitly reported.

Let K be the number of SBs for explicit CSI reporting. The UEestimates/measures/derives the un-quantized or analog explicit CSI usingDL measurement RS (e.g. CSI-RS) for each SB, then constructs a K×Nexplicit CSI matrix as:

${H_{K,N} = \begin{bmatrix}c_{0,0} & c_{0,1} & \ldots & c_{0,{N - 1}} \\c_{1,0} & c_{1,1} & \ldots & c_{1,{N - 1}} \\\vdots & \vdots & \ddots & \vdots \\c_{{K - 1},0} & c_{{K - 1},1} & \ldots & c_{{K - 1},{N - 1}}\end{bmatrix}},$

where c_(s,l) corresponds to the l-th explicit CSI component for SB s.The singular value decomposition of H_(K,N) is performed to represent:H_(K,N)=UΣV^(H)=Σ_(i=0) ^(D-1)σ_(i)u_(i)v_(i) ^(H), where U=[u₀ u₁ . . .u_(K-1)] is the left eigenvector matrix (columns are length-Keigenvectors), V=[v₀ v₁ . . . v_(N-1)] is the right eigenvector matrix(columns are length-N eigenvectors), Σ=diag([σ₀ σ₁ . . . σ_(D-1)]) is adiagonal matrix of singular values sorted as σ₀≥σ₁≥ . . . ≥σ_(D-1), andD=min(K,N). Then, d principal components where 1≤d<D corresponding to“dominant” singular values σ₀, . . . σ_(d-1) and corresponding left andright eigenvector matrices are constructed as: U_(d)=[u₀ u₁ . . .u_(d-1)]; V_(d)=[v₀ v₁ . . . v_(d-1)]; and Σ_(d)=diag([σ₀ σ₁ . . .σ_(d-1)]. The reduced dimensional or compressed explicit CSI matrix isthen given by H_(K,N)≅

_(N)=U_(d)Σ_(d)V_(d) ^(H)=Σ_(i=0) ^(d-1)σ_(i)u_(i)v_(i) ^(H).

To report compressed H_(K,N), the UE uses one of the followingalternatives. In one example of Alt 0, the UE transforms the explicitCSI matrix H_(K,N) as R_(d)=H_(K,N)V_(d), quantizes R_(d) and V_(d)using a codebook, and then reports the quantized matrices to the eNB,which reconstructs the explicit CSI matrix as H_(K,N)=R_(d)V_(d) ^(H).In another example of Alt 1, the UE quantizes U_(d), V_(d), and Σ_(d)using a codebook, and then reports them to the eNB, which reconstructsthe explicit CSI matrix as H_(K,N)=U_(d)Σ_(d)V_(d) ^(H). In the rest ofthe current disclosure, Alt 1 is assumed for explicit CSI reporting. Thepresent disclosure, however, are general and are applicable to Alt 0.

Considering real and imaginary parts of complex numbers separately astwo real numbers, the total number of reported (real) explicit CSIcomponents is 2d(K+N)+R, where R=0 for Alt 0 and R=d for Alt 1. So, thetotal compression achieved before quantization is

$\frac{2\; {KN}}{{2\; {d( {K + N} )}} + R}.$

In one embodiment, the d value is configured to the UE, e.g. viahigher-layer RRC signaling. In another method, the UE reports apreferred d value in the CSI report. In another method, the preferred dvalue is fixed, for example to 1.

In some embodiments of 0-0, in addition to explicit CSI, the UE is alsoconfigured to report CQI or/and RI. In one example, the UE is configuredto report both CQI and RI. For instance, if the UE is configured toreport the explicit CSI type “dominant eigenvectors,” then the UE canalso be configured to report both CQI and RI. In another example, the UEis configured to report only CQI. For instance, if the UE is configuredto report the explicit CSI type “channel” or “covariance matrix,” thenthe UE can also be configured to report CQI only. In this example, therank (RI) for the reported CQI is pre-determined, for example rank=1, orconfigured. In yet another example, the UE can be configured to reportonly RI.

FIG. 9 illustrates an example PCA 900 based explicit CSI feedbackreporting according to embodiments of the present disclosure. Anembodiment of the PCA 900 shown in FIG. 9 is for illustration only. Oneor more of the components illustrated in FIG. 9 can be implemented inspecialized circuitry configured to perform the noted functions or oneor more of the components can be implemented by one or more processorsexecuting instructions to perform the noted functions. Other embodimentsare used without departing from the scope of the present disclosure.

In some embodiments 0-1, the explicit CSI reporting according to theproposed PCA based explicit CSI compression is shown in FIG. 9 (e.g.,Alt 1). The eNB (or gNB) sends the explicit CSI configuration to the UEwhich includes the explicit CSI type (channel, eigenvector, covariancematrix) and the number of principal components (d value). In one exampleof response, the UE derives explicit CSI of the configured type for eachSB in which the UE is configured to report explicit CSI. In anotherexample of response, the UE constructs the explicit CSI matrix H_(K,N)as explained in the aforementioned embodiments 0. In another example ofresponse the UE applies PCA to obtain d principal components U_(d),V_(d), and Σ_(d). In yet another example of response, the UE finallyquantizes (using a codebook) and reports d principal components. The eNB(or gNB) reconstructs the explicit CSI for K SBs asH_(K,N)=U_(d)Σ_(d)V_(d) ^(H).

In some embodiments 1, a UE is configured with a codebook for separatequantization of: columns of U_(d)=[u₀ u₁ . . . u_(d-1)]; columns ofV_(d)=[v₀ v₁ . . . v_(d-1)]; and diagonal elements of Σ_(d)=diag([σ₀ σ₁. . . σ_(d-1)] according to the following embodiments.

In some embodiments 1-0, a UE is configured with a unit-magnitude scalarcodebook to quantize scalar components u_(m,n) and v_(l,k) of orthogonalmatrices U_(d) and V_(d), respectively, where m, l∈{0,1, . . . , d−1},n∈{0,1, . . . , K−1}, and k∈{0,1, . . . , N−1}, according to one orcombinations of the following codebook alternatives. In one example ofcommon codebook, a common scalar codebook is used to quantize the scalarcomponents u_(m,n) and v_(l,k) of U_(d) and V_(d). An example of such acodebook is a uniform codebook over (0, 1). In another example ofseparate codebook, the scalar components u_(m,n) and v_(l,k) of U_(d)and V_(d) are quantized using two separate scalar codebooks or a pair ofscalar codebooks. An example of such scalar codebooks is a uniformcodebook over (0, 1). In yet another example of real codebook, a realscalar codebook is used to quantize real and imaginary parts of complexcomponents of U_(d) and V_(d) separately as two real numbers. An exampleof such a codebook is a uniform codebook over (0, 1). In yet anotherexample of complex codebook, a complex scalar codebook is used toquantize the complex components of U_(d) and V_(d).

In some embodiments 1-0A, an oversampled DFT codebook comprising DFTvectors of length K, i.e.,

$\{ {{{\lbrack {1,e^{\frac{2\pi \; l}{KO}},e^{\frac{2\pi \; l\; 2}{KO}},\ldots \mspace{14mu},e^{\frac{2\pi \; {l{({K - 1})}}}{KO}}} \rbrack \text{:}\mspace{14mu} l} = 0},1,\ldots \mspace{14mu},{{KO}_{K} - 1}} \}$

is used to quantize the columns of U_(d). Similarly, an oversampled DFTcodebook comprising DFT vectors of length M, i.e.,

$\{ {{{\lbrack {1,e^{\frac{2\pi \; l}{{MO}_{M}}},e^{\frac{2\pi \; l\; 2}{{MO}_{M}}},\ldots \mspace{14mu},e^{\frac{2\pi \; {l{({M - 1})}}}{{MO}_{M}}}} \rbrack \text{:}\mspace{14mu} l} = 0},1,\ldots \mspace{14mu},{{MO}_{M} - 1}} \}$

is used to quantize the columns of V_(d). The oversampling factor can be4 for both DFT codebooks (O_(K)=O_(M)=4).

In some embodiments 1-0B, a scalar amplitude codebook and a scalar phasecodebook respectively are used to quantize amplitude and phase ofcomplex components of U_(d) and V_(d) separately. An example of a 2-bitscalar amplitude codebook is C_(A)={1, √{square root over (0.5)},√{square root over (0.25)}, √{square root over (0.125)}}. Anotherexample of a 2-bit scalar amplitude codebook is C_(A)={1, √{square rootover (0.5)}, √{square root over (0.25)}, 0}. An example of a 3-bitscalar amplitude codebook is C_(A)={1, √{square root over (0.5)},√{square root over (0.25)}, √{square root over (0.125)}, √{square rootover (0.0625)}, √{square root over (0.0313)}, √{square root over(0.0156)}, √{square root over (0.0078)}}. Another example of a 3-bitscalar amplitude codebook is C_(A)={1, √{square root over (0.5)},√{square root over (0.25)}, √{square root over (0.125)}, √{square rootover (0.0625)}, √{square root over (0.0313)}, √{square root over(0.0156)}, 0}. An example of a 2-bit scalar phase codebook is QPSK,i.e.,

$\{ {{{e^{\frac{2\pi \; n}{4}}\text{:}\mspace{14mu} n} = 0},1,2,3} \}.$

Another example of a 3-bit scalar phase codebook is 8PSK, i.e.,

$\{ {{{e^{\frac{2\pi \; n}{8}}\text{:}\mspace{14mu} n} = 0},1,{\ldots \mspace{14mu} 7}} \}.$

In one alternative, for each column U_(d), amplitude and phase for all Kcomponents are quantized, and for each column of V_(d), amplitude andphase of all M components are quantized. In another alternative, foreach column U_(d), the strongest of the K components is reported andamplitude and phase of the remaining K−1 components (after normalizationwith the strongest component) are quantized, and similarly, for eachcolumn of V_(d), the strongest of the M components is reported andamplitude and phase of the remaining M−1 components (after normalizationwith the strongest component) are quantized.

In some embodiments 1-1, a UE is configured with a unit-norm vectorcodebook to quantize columns of U_(d) and V_(d) using two separatecodebooks or a pair of vector codebooks, each of which is according toone of the following alternatives. In one example of real codebook, areal vector codebook is used to quantize real and imaginary parts(vectors) of columns of U_(d) or V_(d) separately as two real vectors.In another example of complex codebook, a complex vector codebook isused to quantize columns of U_(d) or V_(d).

In some embodiments 1-2, a UE is configured with a scalar codebook toquantize diagonal entries of Σ_(d) (i.e., σ₀ σ₁ . . . σ_(d-1)) using acodebook over (0, A), where A is a positive number, for example A=10. Anexample of such a codebook is a uniform codebook over (0, A).

Let C_(U) and C_(V) be codebooks for (d) left and right principalcomponents (or singular vectors of H_(K,N)), U_(d) and V_(d),respectively, where codebook C_(U) comprises of a set of matrices ofsize K×d whose columns are unit-norm and orthogonal, and codebook C_(V)comprises of a set of matrices of size N×d whose columns are unit-normand orthogonal.

In some embodiments 1-3a, a UE is configured with two separate codebooksC_(U) and C_(V) for left and right principal components U_(d) and V_(d),respectively, where the codebook configuration is according to one ofthe following alternatives. In one example, both C_(U) and C_(V) arefixed (hence not configured). In another example, C_(U) is configuredand C_(V) is fixed. In yet another example, C_(U) is fixed and C_(V) isconfigured. In yet another example, both C_(U) and C_(V) are configured.This configuration can be via higher-layer (e.g. RRC) signaling or MAClayer (e.g. MAC CE) signaling.

The UE selects two matrices W and X, where W and X belong to C_(U) andC_(V), respectively, to represent/quantize U_(d) and V_(d) and reportsthe selected matrices in addition to the quantized Σ_(d) (i.e., σ₀ σ₁ .. . σ_(d-1)) to the eNB. There are four alternatives for (W, X)reporting. In one example, both C_(U) and C_(V) are singleton (i.e.,comprising of one matrix), hence W and X are not reported. In anotherexample, C_(U) is singleton and C_(V) is non-singleton (i.e., comprisesof multiple matrices), hence W is not reported and X is reported. In yetanother example, C_(U) is non-singleton and C_(V) is singleton, hence Wis reported and X is not reported. In yet another example, both C_(U)and C_(V) are non-singleton, hence both W and X are reported.

Let C_(U″) and C_(V″) be codebooks for left and right orthogonalmatrices (of H_(K,N)), U and V, respectively, where codebook C_(U″)comprises of a set of orthonormal matrices of size K×K, and codebookC_(V″) comprises of a set of orthonormal matrices of size N×N.

In some embodiments 1-3b, a UE is configured with two separate codebooksC_(U′) and C_(V″) for left and right orthogonal matrices U and V,respectively, where the codebook configuration is according to one ofthe four alternatives in the aforementioned embodiments 1-3a. Thisconfiguration can be via higher-layer (e.g. RRC) signaling or MAC layer(e.g. MAC CE) signaling. The UE selects two matrices W and X, where Wand X belong to C_(U′) and C_(V′), respectively, to represent/quantize Uand V and reports the selected matrices in addition to the quantized Σ(i.e., σ₀ σ₁ . . . ) to the eNB according to one of the fouralternatives for (W, X) reporting (in the aforementioned embodiments1-3a). Note that in this sub-embodiment, the number of principalcomponents (i.e. the d value) does not need to be configured to the UE.

In some embodiments 1-3c, a UE is configured with at least one of twoseparate parameters, SubbandBasisConfig and SpatialBasisConfig, toconfigure U_(d) and V_(d), or U and V, respectively, whereSubbandBasisConfig takes values such as 1, 2, . . . , which representK×d for U_(d) or K×K for U matrices whose columns are unit-norm andorthogonal, and SpatialBasisConfig takes values such as 1, 2, . . . ,which represent N×d for V_(d) or N×N for V matrices whose columns areunit-norm and orthogonal. This configuration can be via higher-layer(e.g. RRC) signaling or MAC layer (e.g. MAC CE) signaling. The UEselects two matrices W and X, depending on the configured values ofSubbandBasisConfig and SpatialBasisConfig, respectively, torepresent/quantize U_(d) and V_(d) or U and V, and reports themaccording to one of the four reporting alternatives in theaforementioned embodiments 1-3a.

In some embodiments 1-4a, a UE is configured with a single jointcodebook pair (C_(U), C_(V)) for left and right principal component pair(U_(d),V_(d)), where the codebook configuration is according to one ofthe four alternatives in the aforementioned embodiments 1-3a. Thisconfiguration can be via higher-layer (e.g. RRC) signaling or MAC layer(e.g. MAC CE) signaling. The UE selects a matrix pair (W, X), whichbelongs to (C_(U), C_(V)), to represent/quantize (U_(d), V_(d)) andreports the selected matrix pair in addition to the quantized Σ_(d)(i.e., σ₀ σ₁ . . . σ_(d-1)) to the eNB. There are two alternatives for(W, X) reporting. In one example, (C_(U), C_(V)) is singleton, hence (W,X) is not reported. In another example, (C_(U), C_(V)) is non-singleton,hence (W, X) is reported.

In some embodiments 1-4b, a UE is configured with a single jointcodebook pair (C_(U′), C_(V′)) for orthogonal matrix pair (U,V), wherethe codebook configuration is according to one of the four alternativesin Sub-embodiment 1-3a. This configuration can be via higher-layer (e.g.RRC) signaling or MAC layer (e.g. MAC CE) signaling. The UE selects twomatrices W and X, where W and X belong to C_(U′) and C_(V′),respectively, to represent/quantize U and V and reports the selectedmatrices in addition to the quantized Σ (i.e., σ₀ σ₁ . . . ) to the eNBaccording to one of the two alternatives for (W, X) reporting (in theaforementioned embodiments 1-4a). Note that in this sub-embodiment, thenumber of principal components (i.e. the d value) does not need to beconfigured to the UE.

In some embodiments 1-4c, a UE is configured with a single jointparameter, BasisConfig, to configure (U_(d),V_(d)) or (U, V), whereBasisConfig takes values such as 1, 2, . . . , which represent pairs of:K×d (for U_(d)) or K×K (for U) matrices and N×d (for V_(d)) or N×N (forV) matrices, whose columns are unit-norm and orthogonal. Thisconfiguration can be via higher-layer (e.g. RRC) signaling or MAC layer(e.g. MAC CE) signaling. The UE selects two matrices W and X, dependingon the configured value of BasisConfig, to represent/quantize U_(d) andV_(d) and reports them according to one of the two reportingalternatives in the aforementioned embodiments 1-4a.

In some embodiments 2, a UE is configured with a codebook pair (C_(U),C_(V)) or parameters for (U_(d),V_(d)) according to one ofSub-embodiments 1-3a to 1-4c, and the UE (instead of SVD) performs thefollowing basis expansion in order to derive compressed or reduceddimensional explicit CSI. For each (W, X) in (C_(U), C_(V)) or accordingto the configured parameter, the UE solves the following least-square(LS) problem: min_(s)∥h−As∥², where h=vec(H_(K,N)), A=vec([w₀x₀* w₁x₁* .. . w_(d-1)x_(d-1)*]), W=[w₀ w₁ . . . w_(d-1)], and X=[x₀ x₁ . . .x_(d-1)].

The notation vec(M) transforms matrix M into a vector by concatenatingcolumns of M. The solution to the LS problem is given bys*=(A^(H)A)⁻¹A^(H)h. The UE quantizes s*and reports s*as explicit CSI.The UE may also report a (W, X) pair in (C_(U), C_(V)) or according tothe configured parameter, which achieves the minimum LS over allpossible (W, X) pairs.

In some embodiments 2-0, a UE is configured with a codebook pair(C_(U′), C_(V′)) or parameters for (U, V) according to one ofSub-embodiments 1-3a to 1-4c, and the UE derives and reports s* and a(W, X) pair in (C_(U′), C_(V′)) or according to the configured parametersimilar to the aforementioned embodiments 2, where the length of vectors* is min(K, N).

In some embodiment 3, a UE is configured with a codebook pair (C_(U),C_(V)) or parameters for (U_(d),V_(d)) according to one ofSub-embodiments 1-3a to 1-4c, and the UE (instead of SVD) performs thefollowing derivation in order to derive compressed or reduceddimensional explicit CSI. For each (W, X) in (C_(U), C_(V)) or accordingto the configured parameter, the UE derives S which approximatesH_(K,N)≈WSX^(H), and optimizes one of performance metrics such asmaximum power, maximum SINR and minimum quantization error, where S is ad×d diagonal matrix

$\quad\begin{bmatrix}s_{0} & 0 & 0 & 0 \\0 & s_{1} & 0 & 0 \\0 & 0 & \ddots & 0 \\0 & 0 & 0 & s_{d - 1}\end{bmatrix}$

with non-negative diagonal elements s₀, s₁, . . . , S_(d-1). The UEquantizes s₀, S₁, . . . , S_(d-1) and reports them as explicit CSI. TheUE may also report a (W, X) pair in (C_(U), C_(V)) or according to theconfigured parameter, which achieves the optimal value of the consideredmetric over all possible (W, X) pairs.

In some embodiments 3-0, a UE is configured with a codebook pair(C_(U′), C_(V′)) or parameters for (U,V) according to one ofSub-embodiments 1-3a to 1-4c, and the UE derives and reports S and a (W,X) pair in (C_(U′), C_(V′)) or according to the configured parametersimilar to the aforementioned embodiments 3.

FIG. 10 illustrates an example differential PCA 1000 in a time domainaccording to embodiments of the present disclosure. An embodiment of thedifferential PCA 1000 shown in FIG. 10 is for illustration only. One ormore of the components illustrated in FIG. 10 can be implemented inspecialized circuitry configured to perform the noted functions or oneor more of the components can be implemented by one or more processorsexecuting instructions to perform the noted functions. Other embodimentsare used without departing from the scope of the present disclosure.

In some embodiments 4, a UE is configured to report explicit CSI using adifferential or multi-stage compression techniques such as “differentialPCA” in order to exploit correlation in spatial (across antennas) or/andfrequency (across SBs) or/and time (across subframes) domains. Anexample of differential PCA is shown in FIG. 10 in which the explicitCSI is reported using a two stage differential PCA where differentialPCA is considered in time domain. In one example of PCA1, at time (orsubframe) t, the first stage PCA with d₁ principal components is appliedto compress H_(K,N) ^((t)). The first stage PCA exploits correlationacross SBs and antenna ports. A few example values of d₁ is 1, 2, and 4.Note that PCA1 is an example of the base or coarse layer of amulti-stage or multi-layer or multi-resolution compression scheme. Inanother example of PCA 2, at time (or subframe)>t+n, n=1, 2, . . . , thesecond PCA with d₂ principal components is applied to compress E_(K,N)^((t+n))=H_(K,N) ^((t+n))−H_(K,N) ^((t)). The second stage PCA exploitscorrelation across time in addition to across SBs and antenna ports. Afew example values of d₂ is 1, . . . , d₁. Note that PCA2 is an exampleof the refinement layer of a multi-stage or multi-layer ormulti-resolution compression scheme.

At least one or a combination of the following example is adopted toconfigure d₁ and d₂ to the UE. In one example, both d₁ and d₂ areconfigured to the UE. In another example, both d₁ and d₂ are reported bythe UE in the CSI report. In another example, both d₁ and d₂ are fixedin the specification. For example, d₁ is fixed to 2, and d₂ is fixedto 1. In yet another example, one of d₁ and d₂ is configured and theother is fixed. For example, d₁ is configured and d₂ is fixed to 1. Inyet another example, one of d₁ and d₂ is configured and the other isreported by the UE. For example, d₁ is configured and d₂ is reported bythe UE.

In some embodiments 4-0, to reduce overhead, left and right principalcomponents (U_(d) ₂ and V_(d) ₂ ) of PCA2 are derived/reportedseparately. For example, left and right principal components arereported in alternative CSI reporting instances.

In some embodiments 4-1, a UE is configured with explicit CSI reportingbased on a two stage differential PCA (FIG. 10) according to one of thethree reporting configurations in TABLE 1. In one example of reportingconfiguration 0, both 1^(st) (base or coarse) and 2^(nd) (refinement)explicit CSIs are reported periodically, for example using PUCCH. Inanother example of reporting configuration 1, 1^(st) (base or coarse)explicit CSI is reported aperiodically, for example using PUSCH, and2^(nd) (refinement) explicit CSI is reported periodically, for example,using PUCCH. In yet another example of reporting configuration 2, both1^(st) (base or coarse) and 2^(nd) (refinement) explicit CSIs arereported aperiodically, for example using PUSCH.

TABLE 1 Differential PCA based explicit CSI reporting Reporting 1^(st)explicit CSI reporting 2^(nd) explicit CSI reporting configuration (baseor coarse layer) (refinement layer) 0 periodic periodic 1 aperiodicperiodic 2 aperiodic (base) aperiodic (refinement)

FIG. 11 illustrates an example differential PCA 1100 based explicit CSIfeedback reporting according to embodiments of the present disclosure.An embodiment of the differential PCA 1100 shown in FIG. 11 is forillustration only. One or more of the components illustrated in FIG. 11can be implemented in specialized circuitry configured to perform thenoted functions or one or more of the components can be implemented byone or more processors executing instructions to perform the notedfunctions. Other embodiments are used without departing from the scopeof the present disclosure.

In some embodiments 4-2, the explicit CSI reporting according to theproposed differential PCA based explicit CSI compression is shown inFIG. 11. The eNB (or gNB) sends the explicit CSI configuration to the UEwhich includes the explicit CSI type (channel, eigenvector, covariancematrix) and the number of principal components (d₁ and d₂ values). Inresponse: the UE, at step 0, derives 1^(st) explicit CSI (base orcoarse) of the configured type for each SB in which the UE is configuredto report explicit CSI; the UE, at step 1, constructs the 1^(st)explicit CSI matrix H_(K,N) ^((t)) as explained in the aforementionedembodiments 1; the UE, step 2, applies PCA1 to obtain d₁ principalcomponents U_(d) ₁ , V_(d) ₁ , and Σ_(d) ₁ ; and the UE, at step 3,quantizes (using a codebook) and reports d₁ principal components for1^(st) explicit CSI reporting.

The eNB (or gNB) reconstructs the 1^(st) explicit CSI for K SBs asH_(K,N) ^((t))=U_(d) ₁ Σ_(d) ₁ V_(d) ₁ ^(H). To report subsequent r-th,where r>1, explicit CSI, the UE first derives the differential explicitCSI matrix H_(K,N) ^((r))−U_(d) ₁ Σ_(d) ₁ V_(d) ₁ ^(H) and repeats Steps0-3 above with replacing PCA1 with PCA2 with d₂ principal components.The eNB (or gNB) reconstructs the r-th explicit CSI for K SBs as H_(K,N)^((t+r))=U_(d) ₁ Σ_(d) ₁ V_(d) ₁ ^(H)+U_(d) ₂ Σ_(d) ₂ V_(d) ₂ ^(H).

FIG. 12 illustrates an example differential PCA 1200 across SBsaccording to embodiments of the present disclosure. An embodiment of thedifferential PCA 1200 shown in FIG. 12 is for illustration only. One ormore of the components illustrated in FIG. 12 can be implemented inspecialized circuitry configured to perform the noted functions or oneor more of the components can be implemented by one or more processorsexecuting instructions to perform the noted functions. Other embodimentsare used without departing from the scope of the present disclosure.

In some embodiments 5, a UE is configured to report explicit CSI usingdifferential PCA across SBs. For instance, K SBs is partitioned into Lgroups each with K/L consecutive SBs (where we assume that L divides K)and differential PCA is applied across l=0, 1, . . . , L−1 groups ofSBs. An example of such differential PCA is shown in FIG. 12. Let K/L×Nexplicit CSI matrix for SB group l is denoted as H_(K/L,N) ^((l)). Inthe figure, L SB groups are shown in bold dotted rectangles. Thedifferential PCA is applied is follows. In one example of PCA1, thefirst stage PCA with d₁ principal components is applied to compressH_(K/L,N) ⁽⁰⁾ for SB group l=0. The first stage PCA exploits correlationacross SBs in group l=0 and antenna ports. A few example values of d₁ is1, 2, and 4. In another example of PCA2, the second PCA with d₂principal components is applied to compress E_(K/L,N) ^((l))=H_(K/L,N)^((l))−H_(K/L,N) ⁽⁰⁾ for SB group l>0. The second stage PCA exploitscorrelation SB groups in addition to across SBs and antenna ports. A fewexample values of d₂ is 1, . . . , d₁.

In some embodiments 5-0, the number of SB groups L=K, i.e., each SBgroup comprise of a single SB. In this case, PCA1 is used for explicitCSI reporting of SB 0, and PCA2 is used for explicit CSI reporting ofSBs 1, 2, . . . , K−1.

In some embodiments 5-1, instead of across SB groups 1=0, 1, . . . ,L−1, the differential PCA is applied within each SB group. For example,for SB group l=0 (FIG. 12), PCA1 is used for explicit CSI reporting ofSB 0, and PCA2 is used for explicit CSI reporting of SBs 1, 2, . . . ,K/L−1. For SB group l=1 (FIG. 12), PCA1 is used for explicit CSIreporting of SB K/L, and PCA2 is used for explicit CSI reporting of SBsK/L, . . . , 2K/L−1. This continues for SB groups 3, . . . L−1.

In some embodiments 5-2, the differential PCA is applied across bothtime (subframes) and frequency (SBs) by extending the embodiments ondifferential PCA across time and the embodiments on differential PCAacross frequency.

FIG. 13 illustrates example differential PCA 1300 based on WB explicitCSI according to embodiments of the present disclosure. An embodiment ofthe differential PCA 1300 shown in FIG. 13 is for illustration only. Oneor more of the components illustrated in FIG. 13 can be implemented inspecialized circuitry configured to perform the noted functions or oneor more of the components can be implemented by one or more processorsexecuting instructions to perform the noted functions. Other embodimentsare used without departing from the scope of the present disclosure.

In some embodiment 6, a UE is configured to report explicit CSI usingdifferential PCA across SBs where differential is applied with respectto a WB explicit CSI report h_(WB). An example of such explicit CSIreporting is shown in FIG. 13. In one example, the UE derives the WBcomponent of explicit CSI, h_(WB), using the explicit CSI matrixH_(K,N); constructs the differential explicit CSI E_(K,N), which is anK×N matrix whose k-th row, E_(K,N)(k), is constructed by subtractingh_(WB) from the explicit CSI for SB k, i.e.,E_(K,N)(k)=H_(K,N)(k)−h_(WB); applies differential PCA on E_(K,N)≅

_(N)=U_(d)Σ_(d)V_(d) ^(H); and finally reports quantized h_(WB) andU_(d), Σ_(d), and V_(d) ^(H).

The eNB reconstructs the explicit CSI matrix as

_(N), whose k-th row,

_(N)(k), is constructed by adding h_(WB) to the k-th row of

_(N)=U_(d)Σ_(d)V_(d) ^(H), i.e.,

_(N)(k)=

_(N)(k)+h_(WB).

In some embodiments 6-0, a UE is configured to report explicit CSI usingdifferential PCA in the aforementioned embodiments 6 where differentialPCA is applied to each of L SB groups, each with K/L consecutive SBs(where we assume that L divides K). In this case, the UE reports h_(WB)^((l)) and {tilde over (E)}_(K,N) ^((l)) for each of l=0, 1, . . . , L−1SB groups.

In some embodiment 7, a UE is configured to report explicit CSI usingdifferential PCA where differential is in spatial domain across antennaports. For instance, the total (2N₁N₂) antenna ports can be partitionedinto P partial antenna ports each with 2N₁N₂/P. The explicit CSI for1^(st) partial antenna port (partition 0) is reported using PCA1 with d₁principal components, and that for p-th (where p>1) partial antenna port(partition p−1) is reported using PCA2 with d₂ principal components,where PCA1 and PCA2 area according to some embodiments of thisdisclosure.

In some embodiments 8, a UE is configured to first perform a dimensionreduction from 2N₁N₂ to L spatial channel coefficients, and then applyPCA based compression of L channel coefficients according to someembodiments of this disclosure.

In some embodiments 9, a UE is configured to report explicit CSI basedon PCA compression proposed in some embodiments of this disclosure for amulti-panel antenna array at the eNB.

FIG. 14 illustrates an example multi-panel antenna model 1400 accordingto embodiments of the present disclosure. An embodiment of themulti-panel antenna model 1400 shown in FIG. 14 is for illustrationonly. One or more of the components illustrated in FIG. 14 can beimplemented in specialized circuitry configured to perform the notedfunctions or one or more of the components can be implemented by one ormore processors executing instructions to perform the noted functions.Other embodiments are used without departing from the scope of thepresent disclosure.

BS antenna model is a uniform rectangular panel array, comprisingM_(g)N_(g) panels, as illustrated in FIG. 14. M_(g) is number of panelsin a column. N_(g) is number of panels in a row. Antenna panels areuniformly spaced in the horizontal direction with a spacing of d_(g,H)and in the vertical direction with a spacing of d_(g,V). On each antennapanel, antenna elements are placed in the vertical and horizontaldirection, where N is the number of columns, M is the number of antennaelements with the same polarization in each column.

Antenna numbering on the panel illustrated in FIG. 14 assumesobservation of the antenna array from the front (with x-axis pointingtowards broad-side and increasing y-coordinate for increasing columnnumber). The antenna elements are uniformly spaced in the horizontaldirection with a spacing of d_(H) and in the vertical direction with aspacing of d_(V). The antenna panel is either single polarized (P=1) ordual polarized (P=2).

In some embodiments 9-0, a UE is configured to report explicit CSI(i.e., H_(K,N) for base layer PCA or/and E_(K,N) for differential PCA)for each antenna panel separately, where the explicit CSI for a panel isreported based on PCA compression according to one or a combination ofthe aforementioned embodiments 0-8 of this disclosure. Note that N isthe number of explicit CSI components for each panel.

In some embodiments 9-1, a UE is configured to report explicit CSI(i.e., H_(K,N) for base layer PCA or/and E_(K,N) for differential PCA)for D antenna panels jointly, where d_(g,H)×d_(g,V)≥D>1 and the explicitCSI for D panels is reported based on PCA compression according to oneor a combination of the aforementioned embodiments 0-8 of thisdisclosure. Note that N is the number of explicit CSI components for Dpanels. A few examples of such explicit CSI reporting are as follows. Inone example, D=d_(g,H)×d_(g,V) (i.e. all antenna panels) and the UE isconfigured to report explicit CSI for all antenna panels jointly. Inanother example, D=d_(g,H) (i.e. all antenna panels in horizontaldirection) and the UE is configured to report explicit CSI for allhorizontal antenna panels jointly. In yet another example, D=d_(g,V)(i.e. all antenna panels in vertical direction) and the UE is configuredto report explicit CSI for all vertical antenna panels jointly. In yetanother example, D=2×2 (i.e. 4 adjacent antenna panels forming a square)and the UE is configured to report explicit CSI for 2×2 antenna panelsjointly.

In some embodiments 9-2, a UE is configured to report explicit CSI ofall antenna (d_(g,H)×d_(g,V)) panels by considering differential PCAacross antenna panels where, for example, the differential PCA isconsidered with respect to the antenna panel located at (0,0). In otherwords, if (h, v) is the index of an antenna panel in two-dimension,where h=0, 1, . . . , d_(g,H) and v=0, 1, . . . , d_(g,V), then theexplicit CSI for the antenna panel (0,0) is reported using PCA1 with d₁principal components and that for the antenna panels (h, v), whereeither h≠0 or v≠0, is reported using PCA2 with d₂ principal components.The details about the configuration and CSI reporting of thedifferential PCA across multiple antenna panels are according to someembodiments of this disclosure.

FIG. 15 illustrates an example flow chart of a method 1500 for enablingchannel compression according to embodiments of the present disclosure,as may be performed by a UE (e.g., 111-116 as illustrated in FIG. 1). Anembodiment of the method 1500 shown in FIG. 15 is for illustration only.One or more of the components illustrated in FIG. 15 can be implementedin specialized circuitry configured to perform the noted functions orone or more of the components can be implemented by one or moreprocessors executing instructions to perform the noted functions. Otherembodiments are used without departing from the scope of the presentdisclosure.

As shown in FIG. 15, the method 1500 begins at step 1505. In step 1505,the UE receives CSI feedback configuration information for the CSIfeedback including a spatial channel information indicator for eachsubband (SB). In step 1505, the spatial channel information indicatorcomprises at least one of a downlink channel matrix, a covariance matrixof the downlink channel matrix, or an eigenvector of the covariancematrix of the downlink channel matrix.

Next, the UE in step 1510 determines a CSI matrix H_(K,N) comprising adimension K×N based on the CSI feedback configuration information. Inthis step 1510, K indicates a number of SBs and N indicates a number ofcomponents of the spatial channel information indicator.

Subsequently, the UE in step 1515 identifies the spatial channelinformation indicator based on the CSI matrix H_(K,N). In step 1515, thespatial channel information indicator indicates: a matrix U_(d)=[u₀ u₁ .. . u_(d-1)] comprising d column vectors of dimension K×1; a matrixV_(d)=[v₀ v₁ . . . v_(d-1)] comprising d column vectors of dimensionN×1; and a diagonal matrix

$\Sigma_{d} = \begin{bmatrix}\sigma_{0} & 0 & \ldots & 0 \\0 & \sigma_{1} & \ldots & 0 \\\vdots & \vdots & \ddots & 0 \\0 & 0 & \ldots & \sigma_{d - 1}\end{bmatrix}$

comprising d non-negative real numbers σ₀, σ₁, . . . , σ_(d-1) asdiagonal elements. In step 1515, the d is a positive integer that iseither a predetermined value or configured by the BS via CSI feedbackconfiguration information or reported by the UE in the CSI feedback, andwherein the d is determined in a range given by 1≤d<D, where the D isdetermined as D=min(K, N).

In some embodiments, the UE in step 1515 further identifies the spatialchannel information indicator based on a set of d triples {(u_(i),v_(i), σ_(i)): 0≤i≤d−1} where u_(i) is an eigenvector associated with an(i+1)-th largest eigenvalue of a matrix H_(K,N)H_(K,N) ^(H), u_(i) is aneigenvector associated with an (i+1)-th largest eigenvalue of a matrixH_(K,N) ^(H)H_(K,N), and σ_(i) is a squared-root of the (i+1)-th largesteigenvalue of H_(K,N)H_(K,N) ^(H) or H_(K,N) ^(H)H_(K,N). In suchembodiments, the CSI matrix H_(K,N) is represented based on an equationgiven by H_(K,N)≈{tilde over (H)}_(K,N)=Σ_(i=0) ^(d-1)σ_(i)u_(i)v_(i)^(H).

In some embodiments, the UE in step 1515 identifies the spatial channelinformation indicator based on a set of d pairs {(w_(i), σ_(i)):0≤i≤d−1} where w_(i)=vec(u_(i)v_(i) ^(H)) is a column vector of adimension KN×1, and σ_(i) is a non-negative real number. In suchembodiments, a vector form of the CSI matrix H_(K,N), h=vec(H_(K,N)) isrepresented based on an equation given by h≈{tilde over (h)}=Σ_(i=0)^(d-1)σ_(i)w_(i), where a notation vec(X) denotes a column vector thatis constructed by concatenating columns of a matrix X into a singlecolumn.

In some embodiments, the UE in step 1515 identifies the spatial channelinformation indicator based on a triple of matrices (U_(d), V_(d),Σ_(d)). In such embodiments, the CSI matrix H_(K,N) is represented basedon an equation given by H_(K,N)≈{tilde over (H)}_(K,N)=U_(d)Σ_(d)V_(d)^(H).

In some embodiments, the UE in step 1515 identifies the spatial channelinformation indicator based on a codebook for at least one of U_(d),V_(d), or Σ_(d).

In some embodiments, the UE in step 1515 identifies a first spatialchannel information indicator indicating a first triple of matrices,U_(d) ₁ , V_(d) ₁ , and Σ_(d) ₁ based on a first CSI matrix H_(K,N) ⁽¹⁾.

In some embodiments, the UE in step 1515 identifies a second spatialchannel information indicator indicating a second triple of matrices,U_(d) ₂ , V_(d) ₂ , and Σ_(d) ₂ based on a difference H_(K,N) ⁽²⁾−{tildeover (H)}_(K,N) ⁽¹⁾ between a second CSI matrix H_(K,N) ⁽²⁾ and arepresentation {tilde over (H)}_(K,N) ⁽¹⁾ of the first CSI matrixH_(K,N) ⁽¹⁾ according to the first spatial channel informationindicator. In such embodiments, the difference is determined in at leastone of a time domain or a frequency domain, and (d₁, d₂) satisfiesd₁≥d₂, and wherein at least one of d₁ or d₂ is configured by either apredetermined value or the BS via CSI feedback configurationinformation, or reported by the UE in the CSI feedback;

Finally, the UE in step 1520 transmits the CSI feedback including thespatial channel information indicator indicating U_(d), V_(d), and Σ_(d)over an uplink channel.

In some embodiment, the UE in step 1520 transmits a first CSI feedbackincluding the first spatial channel information indicator indicatingU_(d) ₁ , V_(d) ₁ , and σ_(d) ₁ .

In some embodiments, the UE in step 1520 transmits, to the BS overeither the first uplink channel or a second uplink channel, a second CSIfeedback including the second spatial channel information indicatorindicating U_(d) ₂ , V_(d) ₂ , and Σ_(d) ₂ .

Although the present disclosure has been described with an exemplaryembodiment, various changes and modifications may be suggested to oneskilled in the art. It is intended that the present disclosure encompasssuch changes and modifications as fall within the scope of the appendedclaims.

None of the description in this application should be read as implyingthat any particular element, step, or function is an essential elementthat must be included in the claims scope. The scope of patented subjectmatter is defined only by the claims. Moreover, none of the claims areintended to invoke 35 U.S.C. § 112(f) unless the exact words “means for”are followed by a participle.

What is claimed is:
 1. A user equipment (UE) for a channel stateinformation (CSI) feedback in a wireless communication system, the UEcomprising: a transceiver configured to receive, from a base station(BS), CSI feedback configuration information for the CSI feedbackincluding a spatial channel information (SCI) indicator, wherein the SCIindicator indicates a SCI associated with a downlink (DL) channelmatrix; and at least one processor configured to determine, the SCIindicator that indicates a first set of d basis vectors comprising adimension K×1, a second set of d basis vectors comprising a dimensionN×1, and a set of d coefficients, where K indicates a number of subbands(SBs) and N indicates a number of components of the SCI; and wherein thetransceiver is further configured to transmit, to the BS, the CSIfeedback including the determined SCI indicator indicating the first setof d basis vectors, the second set of d basis vectors, and the set of dcoefficients over an uplink channel.
 2. The UE of claim 1, wherein: theleast one processor is further configured to determine a CSI matrixH_(K,N) comprising a dimension K×N based on the CSI feedbackconfiguration information, and the SCI associated with the DL channelmatrix comprises at least one of the DL channel matrix itself, acovariance matrix of the DL channel matrix, or at least one eigenvectorof the covariance matrix of the DL channel matrix, and wherein: thefirst set of d basis vectors comprises columns of a matrix U_(d)=[u₀ u₁. . . u_(d-1)]; the second set of d basis vectors comprises columns of amatrix V_(d)=[v₀ v₁ . . . v_(d-1)]; and the set of d coefficientscorrespond to diagonal elements of a diagonal matrix$\Sigma_{d} = \begin{bmatrix}\sigma_{0} & 0 & \ldots & 0 \\0 & \sigma_{1} & \ldots & 0 \\\vdots & \vdots & \ddots & 0 \\0 & 0 & \ldots & \sigma_{d - 1}\end{bmatrix}$ where σ₀, σ₁, . . . , σ_(d-1) are non-negative realnumbers.
 3. The UE of claim 2, wherein: the at least one processor isfurther configured to identify the SCI indicator based on a set of dtriples {(u_(i), v_(i), σ_(i)): 0≤i≤d−1} where u_(i) is an eigenvectorassociated with an (i+1)-th largest eigenvalue of a matrixH_(K,N)H_(K,N) ^(H), u_(i) is an eigenvector associated with an (i+1)-thlargest eigenvalue of a matrix H_(K,N) ^(H)H_(K,N), and σ_(i) is asquared-root of the (i+1)-th largest eigenvalue of H_(K,N)H_(K,N) ^(H)or H_(K,N) ^(H)H_(K,N), and the CSI matrix H_(K,N) is represented basedon an equation given by H_(K,N)≅{tilde over (H)}_(K,N)=Σ_(i=0)^(d-1)σ_(i)u_(i)v_(i) ^(H).
 4. The UE of claim 2, wherein: the at leastone processor is further configured to identify the SCI indicator basedon a set of d pairs {(w_(i),σ_(i)): 0≤i≤d−1} where w_(i)=vec(u_(i)v_(i)^(H)) is a column vector of a dimension KN×1, and σ_(i) is anon-negative real number, and a vector form of the CSI matrix H_(K,N),h=vec(H_(K,N)) is represented based on an equation given by h≅{tildeover (h)}=Σ_(i=0) ^(d-1)σ_(i)w_(i) where a notation vec(X) denotes acolumn vector that is constructed by concatenating columns of a matrix Xinto a single column.
 5. The UE of claim 1, wherein: the d is a positiveinteger that is either a predetermined value or configured by the BS viaCSI feedback configuration information or reported by the UE in the CSIfeedback, and the d is determined in a range given by 1≤d<D where the Dis determined as D=min(K, N).
 6. The UE of claim 2, whether the at leastone processor is further configured to identify the SCI indicator basedon a codebook for at least one of U_(d), V_(d), or Σ_(d).
 7. The UE ofclaim 2 wherein: the at least one processor is further configured to:identify a first SCI indicator indicating a first triple of matrices,U_(d) ₁ , V_(d) ₁ , and Σ_(d) ₁ , based on a first CSI matrix H_(K,N)⁽¹⁾; and identify a second SCI indicator indicating a second triple ofmatrices, U_(d) ₂ , V_(d) ₂ , and Σ_(d) ₂ , based on a differenceH_(K,N) ⁽²⁾−{tilde over (H)}_(K,N) ⁽¹⁾ between a second CSI matrixH_(K,N) ⁽²⁾ and a representation {tilde over (H)}_(K,N) ⁽¹⁾ of the firstCSI matrix H_(K,N) ⁽¹⁾ according to the first SCI indicator, thedifference is determined in at least one of a time domain or a frequencydomain and (d₁, d₂) satisfies d₁≥d₂, wherein at least one of d₁ or d₂ isdetermined by either a predetermined value or the BS via CSI feedbackconfiguration information, or the UE in the CSI feedback, and thetransceiver is further configured to: transmit, to the BS, a first CSIfeedback including the first SCI indicator indicating U_(d) ₁ , V_(d) ₁, and Σ_(d) ₁ , over a first uplink channel; and transmit, to the BS, asecond CSI feedback including the second SCI indicator indicating U_(d)₂ , V_(d) ₂ , and Σ_(d) ₂ over at least one of the first uplink channelor a second uplink channel.
 8. A base station (BS) for a channel stateinformation (CSI) feedback in a wireless communication system, the BScomprising: at least one processor; and a transceiver operably connectedto the at least one processor, the transceiver configured to: transmit,to a user equipment (UE), CSI feedback configuration information for theCSI feedback including a spatial channel information (SCI) indicator,wherein the SCI indicator indicates a SCI associated with a downlink(DL) channel matrix; and receive, from the UE, the CSI feedbackincluding the identified SCI indicator indicating a first set of d basisvectors comprising a dimension K×1, a second set of d basis vectorscomprising a dimension N×1, and a set of d coefficients over an uplinkchannel, where K indicates a number of subbands (SBs) and N indicates anumber of components of the SCI.
 9. The BS of claim 8, wherein: theleast one processor is configured to represent a CSI matrix H_(K,N)using the first set of d basis vectors, the second set of d basisvectors, and the set of d coefficients, indicated by the SCI indicator,the CSI matrix H_(K,N) comprises a dimension K×N based on the CSIfeedback configuration information, the SCI associated with the DLchannel matrix comprises at least one of the DL channel matrix itself, acovariance matrix of the DL channel matrix, or at least one aneigenvector of the covariance matrix of the DL channel matrix, andwherein: the first set of d basis vectors comprises columns of a matrixU_(d)=[u₀ u₁ . . . u_(d-1)]; the second set of d basis vectors comprisescolumns of a matrix V_(d)=[v₀ v₁ . . . V_(d-1)]; and the set of dcoefficients correspond to diagonal elements of a diagonal matrix$\Sigma_{d} = \begin{bmatrix}\sigma_{0} & 0 & \ldots & 0 \\0 & \sigma_{1} & \ldots & 0 \\\vdots & \vdots & \ddots & 0 \\0 & 0 & \ldots & \sigma_{d - 1}\end{bmatrix}$ where σ₀, σ₁, . . . , σ_(d-1) are non-negative realnumbers.
 10. The BS of claim 9, wherein: the SCI indicator is identifiedbased on a set of d triples {(u_(i), v_(i), σ_(i)): 0≤i≤d−1} where u_(i)is an eigenvector associated with an (i+1)-th largest eigenvalue of amatrix H_(K,N)H_(K,N) ^(H), u_(i) is an eigenvector associated with an(i+1)-th largest eigenvalue of a matrix H_(K,N) ^(H)H_(K,N), and σ_(i)is a squared-root of the (i+1)-th largest eigenvalue of H_(K,N)H_(K,N)^(H) or H_(K,N) ^(H)H_(K,N), and the CSI matrix H_(K,N) is representedbased on an equation given by H_(K,N)≅{tilde over (H)}_(K,N)=Σ_(i=0)^(d-1)σ_(i)u_(i)v_(i) ^(H).
 11. The BS of claim 9, wherein: the SCIindicator is identified based on a set of d pairs {(w_(i), σ_(i)):0≤i≤d−1} where w_(i)=vec(u_(i)v_(i) ^(H)) is a column vector of adimension KN×1, and σ_(i) is a non-negative real number, and a vectorform of the CSI matrix H_(K,N), h=vec(H_(K,N)), is represented based onan equation given by h≅{tilde over (h)}=Σ_(i=0) ^(d-1)σ_(i)w_(i), wherea notation vec(X) denotes a column vector that is constructed byconcatenating columns of a matrix X into a single column.
 12. The BS ofclaim 8, wherein: the d is a positive integer that is either apredetermined value or configured by the BS via CSI feedbackconfiguration information or reported by the UE in the CSI feedback, andthe d is determined in a range given by 1≤d<D where the D is determinedas D=min(K, N).
 13. The BS of claim 9, wherein: the transceiver isfurther configured to: receive, from the UE, a first CSI feedbackincluding the first SCI indicator indicating U_(d) ₁ , V_(d) ₁ , andτ_(d) ₁ over a first uplink channel; and receive, from the UE, a secondCSI feedback including a second SCI indicator indicating U_(d) ₂ , V_(d)₂ , and Σ_(d) ₂ over at least one of the first uplink channel or asecond uplink channel, the at least one processor is further configuredto: represent a first CSI matrix H_(K,N) ⁽¹⁾ using the first SCIindicator indicating U_(d) ₁ , V_(d) ₁ , and Σ_(d) ₁ ; and represent adifference H_(K,N) ⁽²⁾−{tilde over (H)}_(K,N) ⁽¹⁾ between a second CSImatrix H_(K,N) ⁽²⁾ and a representation {tilde over (H)}_(K,N) ⁽¹⁾ ofthe first CSI matrix H_(K,N) ⁽¹⁾ according to the first SCI indicatorusing the second SCI indicator indicating U_(d) ₂ , V_(d) ₂ , and Σ_(d)₂ , and the difference is determined in at least one of a time domain ora frequency domain, and (d₁, d₂) satisfies d₁≥d₂, wherein at least oneof d₁ or d₂ is configured by either a predetermined value or the BS viaCSI feedback configuration information, or the UE in the CSI feedback.14. A method of a user equipment (UE) for a channel state information(CSI) feedback in a wireless communication system, the methodcomprising: receiving, from a base station (BS), CSI feedbackconfiguration information for the CSI feedback including a spatialchannel information (SCI) indicator, wherein the SCI indicator indicatesa SCI associated with a downlink (DL) channel matrix; determine the SCIindicator that indicates a first set of d basis vectors comprising adimension K×1, a second set of d basis vectors comprising a dimensionN×1, and a set of d coefficients, where K indicates a number of subbands(SBs) and N indicates a number of components of the SCI; andtransmitting, to the BS, the CSI feedback including the determined SCIindicator indicating the first set of d basis vectors, the second set ofd basis vectors, and the set of d coefficients over an uplink channel.15. The method of claim 14, further comprising: determining a CSI matrixH_(K,N) comprising a dimension K×N based on the CSI feedbackconfiguration information, wherein the SCI associated with the DLchannel matrix comprises at least one of the DL channel matrix itself, acovariance matrix of the DL channel matrix, or at least one eigenvectorof the covariance matrix of the DL channel matrix, and wherein: thefirst set of d basis vectors comprises columns of a matrix U_(d)=[u₀ u₁. . . u_(d-1)]; the second set of d basis vectors comprises columns of amatrix V_(d)=[v₀ v₁ . . . v_(d-1)]; and the set of d coefficientscorrespond to diagonal elements of a diagonal matrix$\Sigma_{d} = \begin{bmatrix}\sigma_{0} & 0 & \ldots & 0 \\0 & \sigma_{1} & \ldots & 0 \\\vdots & \vdots & \ddots & 0 \\0 & 0 & \ldots & \sigma_{d - 1}\end{bmatrix}$ where σ₀, σ₁, . . . , σ_(d-1) are non-negative realnumbers.
 16. The method of claim 15, further comprising: identifying theSCI indicator based on a set of d triples {(u_(i), v_(i), σ_(i)):0≤i≤d−1} where u_(i) is an eigenvector associated with an (i+1)-thlargest eigenvalue of a matrix H_(K,N)H_(K,N) ^(H), u_(i) is aneigenvector associated with an (i+1)-th largest eigenvalue of a matrixH_(K,N) ^(H)H_(K,N), and σ_(i) is a squared-root of the (i+1)-th largesteigenvalue of H_(K,N)H_(K,N) ^(H) or H_(K,N) ^(H)H_(K,N), wherein theCSI matrix H_(K,N) is represented based on an equation given byH_(K,N)≅{tilde over (H)}_(K,N)=Σ_(i=0) ^(d-1)σ_(i)u_(i)v_(i) ^(H). 17.The method of claim 15, further comprising: identifying the SCIindicator based on a set of d pairs {(w_(i),σ_(i)): 0≤i≤d−1} wherew_(i)=vec(u_(i)v_(i) ^(H)) is a column vector of a dimension KN×1, andσ_(i) is a non-negative real number, wherein a vector form of the CSImatrix H_(K,N), h=vec(H_(K,N)) is represented based on an equation givenby h≅{tilde over (h)}=Σ_(i=0) ^(d-1)σ_(i)w_(i) where a notation vec(X)denotes a column vector that is constructed by concatenating columns ofa matrix X into a single column.
 18. The method of claim 14, wherein:the d is a positive integer that is either a predetermined value orconfigured by the BS via CSI feedback configuration information orreported by the UE in the CSI feedback, and the d is determined in arange given by 1≤d<D where the D is determined as D=min(K, N).
 19. Themethod of claim 15, further comprising identifying the SCI indicatorbased on a codebook for at least one of U_(d), V_(d), or Σ_(d).
 20. Themethod of claim 15, further comprising: identifying a first SCIindicator indicating a first triple of matrices, U_(d) ₁ , V_(d) ₁ , andΣ_(d) ₁ based on a first CSI matrix H_(K,N) ⁽¹⁾; identifying a secondSCI indicator indicating a second triple of matrices, U_(d) ₂ , V_(d) ₂, and Σ_(d) ₂ based on a difference H_(K,N) ⁽²⁾−{tilde over (H)}_(K,N)⁽¹⁾ between a second CSI matrix H_(K,N) ⁽²⁾ and a representation {tildeover (H)}_(K,N) ⁽¹⁾ of the first CSI matrix H_(K,N) ⁽¹⁾ according to thefirst SCI indicator, wherein the difference is determined in at leastone of a time domain or a frequency domain and (d₁, d₂) satisfies d₁≥d₂,and wherein at least one of d₁ or d₂ is determined by either apredetermined value or the BS via CSI feedback configurationinformation, or the UE in the CSI feedback; transmitting, to the BS, afirst CSI feedback including the first SCI indicator indicating U_(d) ₁, V_(d) ₁ , and Σ_(d) ₁ over a first uplink channel; and transmitting,to the BS, a second CSI feedback including the second SCI indicatorindicating U_(d) ₂ , V_(d) ₂ , and Σ_(d) ₂ over either the first uplinkchannel or a second uplink channel.